Description

You will design, develop, and maintain scalable batch and real-time data pipelines on AWS, building reliable data lake and warehouse solutions.

This role is remote.

Responsibilities

• Build and manage data lake and data warehouse solutions using Amazon S3, Redshift, and Glue.
• Develop ETL and ELT workflows using AWS Glue, Lambda, Python, PySpark, and SQL.
• Implement workflow orchestration using Apache Airflow, AWS Step Functions, or similar tools.
• Optimize data pipelines, SQL queries, storage formats, and cloud resource utilization.
• Build secure data solutions using AWS IAM, KMS, VPC, and access-control policies.

Required Skills

• 6+ years of experience in data engineering and cloud-based data platforms.
• Strong expertise in AWS services: S3, Redshift, Glue, RDS, Athena, DynamoDB.
• Proficiency in Python, PySpark, and SQL for data transformation and analysis.
• Experience with ETL/ELT pipeline design and large-scale data processing.
• Knowledge of data modeling, data warehousing, and data lakes.
• Familiarity with Snowflake for data warehousing solutions.
• Understanding of data quality checks, error handling, and audit logging.

Preferred Skills

• Experience with CI/CD pipelines for data engineering workloads.
• Background in supporting data migration from on-premises or other cloud platforms.

Key Skills

Education

Not specified