Description

You will design, build, and maintain scalable data architectures and processing pipelines for self-service analytics.

This role is hybrid.

Responsibilities

• Build and maintain batch and real-time data pipelines using AWS services.
• Design and develop ETL frameworks for scalable data processing and modeling.
• Implement data modeling on Redshift, Snowflake, or Databricks.
• Create reusable data sources and dashboards to enable self-service analytics.

Required Skills

• 6+ years of hands-on data engineering experience.
• Expertise with AWS services: S3, Redshift, EMR, Glue, Kinesis, DynamoDB.
• Proficiency in Python and SQL for data processing and analysis.
• Experience with SQL Server.
• Knowledge of AWS Athena, Data Lake, and Lakehouse architectures.
• Any Graduate degree.

Preferred Skills

• Experience with Informatica, Talend, or Fivetran for ETL development.
• Experience with Databricks for Spark workloads or Snowflake.
• Working knowledge of Big Data processing, CI/CD setup, and Infrastructure-as-Code.

Key Skills

Education

Any Graduate