Design, develop, and maintain ETL/ELT data pipelines to support business reporting, analytics, and operational needs.

Write, optimize, and troubleshoot complex SQL queries, stored procedures, views, and database objects.

Assist with developing and supporting data pipelines using Python, Snowflake, AWS, Informatica or Apache Airflow/Astronomer, and dbt

Support data ingestion, transformation, validation, and loading processes across multiple data sources.

Assist with data warehouse development, including dimensional modeling, fact tables, and dimension tables.

Monitor production data pipelines and investigate data quality, performance, and reliability issues.

Participate in on-call support rotations, incident triage, root cause analysis (RCA), and issue resolution activities.

Provide Level 1 production support for data pipelines, ETL processes, data warehouse objects, and reporting solutions.

Perform routine maintenance activities, including job validation, configuration updates, data reconciliations, deployment validation, and system health checks.

Analyze alerts, logs, and monitoring dashboards to identify and resolve operational issues proactively.

Create and maintain operational documentation, runbooks, support procedures, and knowledge base articles.

Escalate complex issues to senior engineers while providing detailed troubleshooting findings.

Collaborate with data engineers, analysts, and business stakeholders to deliver reliable and scalable data solutions.

Contribute to documentation, code reviews, testing activities, and continuous improvement initiatives.

• Follow engineering best practices for development, deployment, monitoring, support, and maintenance.