AWS Data Engineer (Spark Scala)

Job Description

About The Opportunity We are a fast-growing provider of cloud data engineering services within the Information Technology & Services sector. Our teams build high-throughput data platforms on Amazon Web Services for Fortune 500 and digitally native clients across retail, fintech, and healthcare. Leveraging open-source big-data frameworks and modern DevOps practices, we turn raw, real-time streams into actionable insights that drive mission-critical decisions. Role & Responsibilities Design, build, and optimize secure AWS data lakes and lakehouses for petabyte-scale analytics. Develop Spark (Scala) ETL jobs on EMR/Glue, ensuring efficient ingestion, transformation, and partitioning. Implement automated data quality checks, schema validation, and performance tuning for sub-second query latency. Orchestrate pipelines with AWS Step Functions, Airflow, and CI/CD to enable reliable, repeatable deployments. Collaborate with Data Scientists to productionize machine-learning features and batch/stream jobs. Document architecture, promote engineering best practices, and mentor junior engineers on cloud-native patterns. Skills & Qualifications Must-Have 4+ years designing data solutions on AWS (S3, Glue, EMR, Redshift, Lake Formation). Expertise in Spark with Scala, including performance diagnostics and cluster optimization. Proven experience building end-to-end ETL/ELT pipelines and implementing data governance. Strong SQL skills and exposure to columnar file formats (Parquet, ORC). Hands-on with Terraform/CloudFormation, Git, and automated testing frameworks. Bachelor’s degree in Computer Science, Engineering, or equivalent. Preferred Real-time streaming with Kafka/Kinesis and Lambda. Experience migrating on-prem Hadoop workloads to AWS. Knowledge of Delta Lake, Iceberg, or Hudi table formats. Exposure to ML Ops and feature stores on SageMaker. Benefits & Culture Highlights On-site innovation lab equipped with the latest AWS tooling for rapid prototyping. Dedicated learning budget covering AWS certifications and industry conferences. Collaborative, high-trust culture that rewards thought leadership and measurable impact. Location: On-site, India — join us to architect the next generation of cloud-native data platforms and accelerate your career as a Senior AWS Data Engineer. Skills: aws step functions,sql,hudi,apache airflow,terraform,kafka,aws,aws data engineer (spark scala),iceberg,git,delta lake,kinesis,lambda,spark,scala,python,etl,cloudformation