Job description Job Summary We are seeking an experienced Infra. Architect with 8 to 11 years of experience to join our dynamic team. The ideal candidate will have expertise in Infra CI CD Pipelines Bicep Azure DevOps Terraform PowerShell and ARM. This role requires domain experience in Operations and Process Manufacturing Industry. The work model is hybrid with day shifts and no travel required. read more Key Skills kubernetescontinuous developmentaksmicrosoft azureci/cdeksazure devopsinfrastructure architecturecloudscriptingautomationcollaborationinfrastructuredevopspowershellcloud infrastructuretroubleshootingterraformawsarmci cd pipelinecommunication skills

Job description Must Have: 35 years of hands-on experience as a Data Engineer Ability to work as an individual contributor, delivering features/stories within deadlines and quality standards Strong understanding of the Agile development process Excellent programming skills and proficiency in writing complex SQL queries Fast learner with the ability to grasp new tools and technologies in the data engineering ecosystem Good communication skills and ability to interact with clients directly Technical Skills: Programming Languages: Java / Python Big Data Technologies: Spark / PySpark, Hadoop, Hive, YARN, Oozie Cloud Platforms & Services: Cloud data warehouse: Snowflake AWS: EMR, S3, Lambda, RDS/Aurora Testing Frameworks: JUnit, Mockito, PowerMock Databases / Querying: Proficient in SQL across platforms: MySQL, SQL Server, Oracle, Hadoop, Snowflake Version Control: GitHub Project Management Tools: VSTS (Azure DevOps Boards) Build Tools: Maven / Gradle CI/CD Tools: Azure DevOps Pipelines Added Advantage: Prior experience with end-to-end data pipelines in production environments Familiarity with data modeling, ETL design, and real-time data streaming Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: Any Graduate Key Skills Skills highlighted with ‘‘ are preferred keyskills Data EngineeringPython PysparkJavaAWS

Job description Skills Required: Should have a minimum 3+ years in Data Engineering, Data Analytics platform. Should have strong hands-on design and engineering background in AWS, across a wide range of AWS services with the ability to demonstrate working on large engagements. Should be involved in Requirements Gathering and transforming them to into Functionally and technical design. Maintain and optimize the data infrastructure required for accurate extraction, transformation, and loading of data from a wide variety of data sources. Design, build and maintain batch or real-time data pipelines in production. Develop ETL/ELT Data pipeline (extract, transform, load) processes to help extract and manipulate data from multiple sources. Automate data workflows such as data ingestion, aggregation, and ETL processing and should have good experience with different types of data ingestion techniques: File-based, API-based, streaming data sources (OLTP, OLAP, ODS etc) and heterogeneous databases. Prepare raw data in Data Warehouses into a consumable dataset for both technical and nontechnical stakeholders. Strong experience and implementation of Data lakes, Data warehousing, Data Lakehousing architectures. Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. Monitor data systems performance and implement optimization strategies. Leverage data controls to maintain data privacy, security, compliance, and quality for allocated areas of ownership. Experience of AWS tools (AWS S3, EC2, Athena, Redshift, Glue, EMR, Lambda, RDS, Kinesis, DynamoDB, QuickSight etc.). Strong experience with Python, SQL, pySpark, Scala, Shell Scripting etc. Strong experience with workflow management & Orchestration tools (Airflow, Should hold decent experience and understanding of data manipulation/wrangling techniques. Demonstrable knowledge of applying Data Engineering best practices (coding practices to DS, unit testing, version control, code review). Big Data Eco-Systems, Cloudera/Hortonworks, AWS EMR etc. Snowflake Data Warehouse/Platform. Streaming technologies and processing engines, Kinesis, Kafka, Pub/Sub and Spark Streaming. Experience of working with CI/CD technologies, Git, Jenkins, Spinnaker, Ansible etc Experience building and deploying solutions to AWS Cloud. Good experience on NoSQL databases like Dynamo DB, Redis, Cassandra, MongoDB, or Neo4j etc. Experience with working on large data sets and distributed computing (e.g., Hive/Hadoop/Spark/Presto/MapReduce). Good to have working knowledge on Data Visualization tools like Tableau, Amazon QuickSight, Power BI, QlikView etc. Experience in Insurance domain preferred. Role: Data Engineer Industry Type: Insurance Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: Any Graduate PG: Any Postgraduate Doctorate: Any Doctorate Key Skills Skills highlighted with ‘‘ are preferred keyskills PysparkAWSPythonSQL Data Engineeringdata engineer