Data Engineer – AWS + Hadoop

Synechron — Bengaluru - Bellandur (GTP)

Job Summary Synechron is seeking a Data Engineer – AWS + Hadoop to build and optimize scalable data pipelines, data lake solutions, and distributed data platforms. This role supports analytics, machine learning, and reporting by delivering reliable, secure, and cost-efficient data solutions. Software Requirements Required AWS : S3, Glue, EMR, Athena, Lambda, Redshift, IAM, CloudWatch Hadoop ecosystem : HDFS, Hive, Spark, Kafka, Oozie and/or Airflow Spark with PySpark and/or Scala SQL , Python or Scala , Shell scripting Kafka and/or Kinesis Airflow and/or AWS Step Functions Git , Docker CI/CD using Jenkins or GitHub Actions Experience with data modeling, partitioning, metadata, and data quality checks Knowledge of security and governance including IAM, encryption, RBAC, and PII handling Preferred Lake Formation Curated data APIs or analytics views Cost optimization and advanced observability practices Overall Responsibilities Design and implement ETL/ELT pipelines for batch and streaming workloads Build ingestion frameworks using Kafka/Kinesis and Spark Develop and optimize AWS-based data lakes and warehouses Manage Hadoop ecosystem tools and job orchestration Implement data quality, governance, and access controls Monitor pipelines and improve cost, performance, and reliability Collaborate with analytics, ML, and BI teams to deliver curated datasets Participate in code reviews, documentation, and engineering standards Technical Skills (By Category) Programming Languages Essential: SQL, Python and/or Scala, Shell scripting Preferred: Advanced PySpark optimization Databases / Data Management Essential: Data modeling, schema design, partitioning, metadata management, Redshift, Hive Preferred: Curated data services and advanced cataloging Cloud Technologies Essential: AWS data services including S3, Glue, EMR, Athena, Lambda, Redshift, IAM, CloudWatch Preferred: Lake Formation and cost optimization strategies Frameworks and Libraries Essential: Spark, Kafka/Kinesis,

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