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Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSCloudDockerETLKubernetesPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Design, develop, and maintain ETL/ELT pipelines using SQL, Python, and Spark
- Build and manage data workflows using Apache Airflow for orchestration and scheduling
- Develop scalable and optimized solutions using AWS services (S3, Glue, Redshift, EMR, Lambda, etc.)
- Implement and manage data processing pipelines in Databricks (Delta Lake, notebooks, workflows, Unit Catalog)
- Ensure data quality, reliability, and performance across pipelines
- Collaborate with analytics, product, and business teams to deliver data solutions
- Monitor, troubleshoot, and optimize production pipelines
Requirements
What you’ll need- Strong proficiency in SQL and Python
- Hands-on experience with Apache Spark (PySpark preferred)
- Experience working with Apache Airflow for workflow orchestration
- Solid experience with AWS cloud platform. Redshift performance optimization skills
- Hands-on experience in Databricks
- Understanding of data warehousing, data modeling, and ETL design
- Experience with CI/CD pipelines and GitHub Actions (Good to Have)
- Knowledge of Pharmaceutical / Life Sciences domain (Good to Have)
- Familiarity with data governance and quality frameworks (Good to Have)
- Exposure to Docker, Kubernetes, or similar technologies (Good to Have)
Benefits
Comp & perks- Flexible Work Arrangements
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythonApache SparkApache AirflowAWSRedshiftDatabricksETLdata modelingCI/CD
Soft Skills
collaborationtroubleshootingoptimizationdata quality assurance