Lead Data Engineer with AWS

2 weeks ago

Alappuzha, India People Prime Worldwide Full time

Senior Data Engineer- (Python & AWS (Simplified JD) Experience: 7–16 years Location : Hyderabad Job Summary We are looking for a Senior Data Engineer who can build, maintain, and optimize large-scale data systems using AWS and Python. You will design data pipelines, ensure data quality, automate workflows, and support analytics/AI teams. The role needs strong technical expertise and leadership. Key Responsibilities (Simplified) - Build and manage scalable data pipelines using AWS Glue, Lambda, EMR, Step Functions, Redshift. - Create and optimize data lakes and data warehouses on AWS (S3, Redshift, Athena). - Develop ETL/ELT processes using Python (pandas, PySpark). - Integrate data from various sources like RDBMS, APIs, Kafka/Kinesis. - Design efficient data models and schemas. - Ensure data quality, monitoring, and lineage using AWS tools. - Implement data governance, security, and compliance (IAM, encryption). - Work with Data Science, Analytics, Product, and DevOps teams. - Set up CI/CD for data pipelines. - Mentor junior engineers and review their code. - Monitor system performance and handle troubleshooting. Required Skills - Bachelor’s/Master’s degree in Computer Science or related field. - 5–10 years of experience in data engineering. - Strong Python skills (pandas, PySpark, boto3, SQLAlchemy). - Expertise with AWS services: Glue, Lambda, EMR, Step Functions, Redshift, Athena, S3, Kinesis, DynamoDB. - Strong SQL and data modeling skills. - Experience building data lakes, warehouses, and streaming solutions. - Knowledge of ETL best practices. - Experience with Git and CI/CD pipelines. - Understanding of Docker/Kubernetes and DevOps concepts. - Good communication and problem-solving skills. Nice-to-Have Skills - Spark / PySpark on EMR or Glue. - Airflow, dbt, or Dagster. - Kafka / Kinesis streaming. - AWS Lake Formation, Glue Studio, DataBrew. - SageMaker or QuickSight integration. - AWS Certifications (optional)

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