Description

You will design and build scalable data solutions across our AWS environment.

Responsibilities

• Design and develop ETL/ELT pipelines for data ingestion, processing, and transformation from diverse sources into AWS data warehouses and data lakes.
• Architect and optimize scalable data architectures using data lakes (S3, Delta Lake, Iceberg) and data warehouses (Redshift, Snowflake) on AWS.
• Collaborate with data scientists and analysts to define data models and schemas supporting data-driven decision-making.
• Implement data quality and governance practices to ensure data accuracy and compliance.
• Troubleshoot complex data pipeline failures and recommend system improvements.

Required Skills

• 5+ years experience as a Data Engineer focused on AWS cloud services for data solutions.
• Expertise in designing and optimizing complex data pipelines using AWS Glue, Lambda, EMR, S3, Redshift, Athena, Step Functions, DynamoDB, and Lake Formation.
• Proficiency in Python (including PySpark) and SQL (advanced, query tuning).
• Experience with big data technologies such as Apache Spark, Hadoop, and Kafka.
• In-depth knowledge of data modeling techniques (relational, dimensional) and schema design.
• Experience with containerization using Docker and Kubernetes.
• Familiarity with DevOps practices and CI/CD pipelines (AWS CodePipeline, Jenkins).
• Demonstrated experience supporting ML/AI projects, including feature engineering pipelines.
• Strong skills in problem-solving, analytical thinking, and cross-functional communication.

Key Skills

Education

Any Gradute