We’re hiring a Senior Data Engineer (6–8 years) to lead development and maintenance of scalable data systems on AWS. You’ll work across the full data pipeline—designing, building, and optimizing for reliability, speed, and data quality—supporting analytics and business needs. Key Responsibilities: Build data pipelines using Spark, Scala , and Airflow (DAGs) . Clean, transform, and prepare data; automate workflows using Python . Manage data infrastructure on AWS (S3, Redshift, EMR, Glue, Athena, IAM, EC2) . Work with the Analytics team to deliver data solutions. Develop backend services in Node.js and TypeScript ; manage configs using YAML . Set up CI/CD with GitHub Actions ; monitor and troubleshoot pipelines. Implement data quality checks ; design data lakes and warehouses. Write and optimize SQL queries; handle OLAP/OLTP systems. Process real-time data using Kafka or similar technologies. Stay current with data engineering tools; mentor junior engineers. Help define data governance and best practices. Requirements: Bachelor’s/Master’s in Computer Science or related field. 6–8 years in data engineering with strong skills in Spark, Scala, Python, SQL , and AWS . Experience with Airflow , Node.js , TypeScript , YAML , GitHub Actions , and Kafka . Strong understanding of data warehousing, streaming, and backend systems. Excellent problem-solving and collaboration skills. Bonus Skills: Experience with Azure, GCP , Delta Lake, Apache Iceberg , Flink, Kinesis , Terraform , Docker, Kubernetes , Prometheus, Grafana , and data quality tools.
Job Title
Senior Data Engineer