Key Roles of a Senior Data Engineer

1 day ago

guntur, India beBeeDataEngineer Full time

Key Roles of a Senior Data EngineerWe are building the future of healthcare analytics. Our goal is to create robust data pipelines that power nationwide analytics and support our machine learning systems. These pipelines must be reliable, observable, and continuously improving in production.As a Senior Data Engineer, you will design, build, and maintain scalable ETL pipelines using Python (Pandas, PySpark) and SQL, orchestrated with Airflow.Develop and maintain the data lake on AWS, ensuring quality, governance, scalability, and accessibility.Run and optimize distributed data processing jobs with Spark on AWS EMR and/or EKS.Implement batch and streaming ingestion frameworks (APIs, databases, files, event streams).Enforce validation and quality checks to ensure reliable analytics and ML readiness.Monitor and troubleshoot pipelines with CloudWatch, integrating observability tools like Grafana, Prometheus, or Datadog.Automate infrastructure provisioning with Terraform, following AWS best practices.Manage SQL Server, PostgreSQL, and Snowflake integrations into the data lake.Required Skills and Qualifications:5+ years in data engineering, ETL pipeline development, or data platform roles (flexible for exceptional candidates).Experience designing and operating data lakes or Lakehouse architectures on AWS (S3, Glue, Lake Formation, Delta Lake, Iceberg).Strong SQL skills with PostgreSQL, SQL Server, and at least one AWS cloud warehouse (Snowflake or Redshift).Proficiency in Python (Pandas, PySpark); Scala or Java a plus.Hands-on with Spark on AWS EMR and/or EKS for distributed processing.Strong background in Airflow for workflow orchestration.Expertise with AWS services: S3, Glue, Lambda, Athena, Step Functions, ECS, CloudWatch.Proficiency with Terraform for IaC; familiarity with Docker, ECS, and CI/CD pipelines.Experience building monitoring, validation, and alerting into pipelines with CloudWatch, Grafana, Prometheus, or Datadog.Strong communication skills and ability to collaborate with data scientists, analysts, and product teams.Benefits:The ideal candidate will have a strong background in data engineering and a passion for building scalable and reliable data pipelines.Others:Please note that this role requires a strong team player who can work collaboratively with data scientists, analysts, and product teams.],

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