Big Data Engineer

Job description Key Responsibilities: Design, build, and optimize large-scale data processing systems using distributed computing frameworks like Hadoop, Spark, and Kafka. Develop and maintain data pipelines (ETL/ELT) to support analytics, reporting, and machine learning use cases. Integrate data from multiple sources (structured and unstructured) and ensure data quality and consistency. Collaborate with cross-functional teams to understand data needs and deliver data-driven solutions. Implement data governance, data security, and privacy best practices. Monitor performance and troubleshoot issues across data infrastructure. Stay updated with the latest trends and technologies in big data and cloud computing. Required Qualifications: Bachelors or Master’s degree in Computer Science, Engineering, or a related field. 6+ years of experience in big data engineering or a similar role. Proficiency in big data technologies such as Hadoop, Apache Spark, Hive, and Kafka. Strong programming skills in Python. Experience with cloud platforms like AWS (EMR, S3, Redshift), GCP (BigQuery, Dataflow), or Azure (Data Lake, Synapse). Solid understanding of data modeling, ETL/ELT processes, and data warehousing concepts. Familiarity with CI/CD tools and practices for data engineering. Preferred Qualifications: Experience with orchestration tools like Apache Airflow or Prefect. Knowledge of real-time data processing and stream analytics. Exposure to containerization tools like Docker and Kubernetes. Certification in cloud technologies (e.g., AWS Certified Big Data – Specialty). Role: Big 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 PysparkHadoopSparkHdfsPython HiveBig DataSQL