Job description About the Role: Take your software engineering career to the next level as a Senior Product Software Engineer. You will play a key role in designing, developing, and troubleshooting software programs. Your technical skills and innovative mindset will contribute to the continuous improvement of our products, making a significant impact on user experience and satisfaction. Responsibilities: Take the lead in designing, developing, and maintaining complex software applications to meet project requirements. Collaborate with cross-functional teams to define design specifications and details, taking into account diverse perspectives. Regularly communicate project updates, progress, and challenges to stakeholders and team members. Prepare detailed technical specifications and requirements documents to guide the development process. Identify bottlenecks and optimize software programs to improve overall performance and efficiency. Lead the design of innovative and user-friendly software applications that align with customer needs and industry standards. Create comprehensive testing routines and procedures to ensure the reliability and accuracy of software applications. Utilize mathematical principles and statistical approaches to solve intricate problems in scientific or applied fields within software projects. Collaborate with others to troubleshoot and resolve complex information technology issues that may arise during development. Prepare and preprocess data for analysis, ensuring its accuracy and readiness for use in software applications. Offer technical support to end-users, providing assistance for software maintenance, troubleshooting, and usage queries. Skills: Software Engineering: The ability to design, develop, and maintain software systems and applications by applying principles and techniques of computer science, engineering, and mathematical analysis. This includes the capacity to understand user requirements, create and test the software, and resolve any software-related issues. Software Development: The ability to design, write, test, and implement software programs, applications, and systems. This includes understanding various programming languages, software architecture, and software testing methods. It also involves problem-solving capabilities to fix software issues and improve functionality. Programming: The ability to design, write, test, debug, and maintain the instructions, also known as code, that a computer must follow to execute a task. This skill often involves various programming languages such as Python, Java, or C++. Problem Solving: The ability to understand a complex situation or issue and devise a solution by defining the problem, identifying potential strategies, and ultimately choosing and implementing the most effective course of action. Analysis: The ability to examine complex situations or problems, break them down into smaller parts, and understand how these parts work together. Testing: The skill of evaluating a system or process, often in software or product development. It involves the ability to identify problems, measure effectiveness, and ensure quality or functionality. Agile: The ability to swiftly and effectively respond to changes, with an emphasis on continuous improvement and flexibility. In the context of project management, it denotes a methodology that promotes adaptive planning and encourages rapid and flexible responses to changes. Source Code Repository: The ability to effectively use a source code repository, a file archive and web hosting facility where a large amount of source code, for software or for web pages, is kept, either publicly or privately. This skill involves the ability to manage and track changes to code, identify and fix issues, merge code from different branches, and collaborate with other developers. Relational Database: The ability to design, implement, and manipulate a relational database, a type of database that stores and organizes data in a structured way and where data is logically inter-related. This skill often requires profic

Job description Service Engineer - is responsible to support all service and support activities related to the client OP Center platforms under service of IT This includes the appropriate technical handling of incident and task tickets raised via SNOW, the technically proficient handling and resolution of issues, patches, technical inquiries, monitoring tasks, account requests and other service related activites Appropriate and service- oriented end user interaction as well as the cooperation within the client IT teams and business stakeholders Execution of evolutionary maintenance activities and change requests for the implementation of system improvements read more Key Skills Business transformationXMLAgileInstrumentationSchedulingUnit testingOracleAnalyticsMonitoring

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks

Job description Overview We are looking for a Data Engineering Lead who thrives in solving complex data challenges and building scalable, high-performance data solutions. This role is ideal for someone with deep expertise in Databricks, PySpark, SQL, and cloud data platforms such as AWS or Azure. You will lead a team of skilled data engineers to design and implement robust, cloud-native data pipelines and drive data architecture strategy that empowers real-time and strategic business decisions. If you are passionate about big data, cloud technologies, and mentoring engineers while building impactful solutionswe want you on our team! Key Responsibilities Lead the design and implementation of scalable data pipelines using Databricks and PySpark Build efficient ETL/ELT processes for seamless data ingestion and transformation across systems Work with product and analytics teams to gather and translate business data requirements into technical solutions Architect and optimize cloud-based data lakes and warehouses on AWS or Azure Guide and mentor junior data engineers, conduct code reviews, and enforce coding best practices Continuously evaluate and integrate new tools, technologies, and frameworks to enhance data workflows Ensure data integrity, security, and compliance across all solutions Collaborate cross-functionally with data scientists, analysts, and DevOps teams Drive performance tuning and operational excellence in deployed pipelines and data infrastructure Contribute to defining and executing the long-term data strategy for the organization Required Skills Experience 4+ years of hands-on experience in Databricks, PySpark, and SQL on AWS or Azure Strong programming skills in Python with good understanding of software engineering principles Solid knowledge of data warehousing concepts, structured/unstructured data, and big data ecosystems Proven experience with cloud data lakes and data pipeline development in a production environment Expertise in building ETL/ELT workflows, including orchestration and automation Experience designing data models that support reporting, analytics, and machine learning Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git) Excellent problem-solving, analytical thinking, and communication skills Proven ability to lead and mentor technical teams in a collaborative environment Preferred Qualifications Experience with Apache Airflow, Delta Lake, Snowflake, or Azure Synapse Understanding of data governance, lineage, and compliance practices Familiarity with Agile/Scrum methodologies Exposure to real-time streaming data technologies such as Kafka, Spark Streaming Location: Bangalore, Gurgaon, Pune, Mumbai, Delhi, Chennai, Hyderabad, Kolkata, Noida, Ahmedabad Notice Period: Immediate to 15 Days Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: B.Tech/B.E. in Any Specialization PG: Any Postgraduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering Azure SynapseApache AirflowCI/CD pipelinesPySparkDelta LakeSnowflakeDatabricks