Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Create and deploy data products from multiple sources for analytics and reporting, integrating multiple sources to support BI, analytic tools, and SaaS applications.
• Collaborate with data scientists, analysts, and business stakeholders to provide high-quality data engineering support.
• Ensure data quality, integrity, and security across all systems.
• Monitor and troubleshoot data workflows for performance and reliability.
• Translate business specifications into design/code and write complex queries.
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Qualifications

• Proficiency in Python, PySpark, and SQL, including complex query writing.
• Experience with ETL tools and frameworks for data processing.
• Knowledge of cloud platforms such as AWS (Athena, S3, Glue, Lambda, SageMaker, CloudTrail).
• Familiarity with lakehouse architectures (e.g., Dremio) and Workday (a plus).
• Version control and project management tools: Jira, GitHub.
• Ability to develop automation scripts for data workflows.
• Robust debugging and troubleshooting capabilities.
• Excellent problem-solving and communication skills.

Required Skills :

Basic Qualification :

Additional Skills :

Background Check : No

Drug Screen : No

N/A

Stipend :false