Job Title: Sr. Data Engineer Experience: 5 7 years
Location: Hybrid Employment Type: Full-time
Mandatory skills:AWS, Python, SQL, Databricks Experience in Clinical Domain / Clinical datasets
About the Role
We are looking for a highlyskilled Senior Data Engineer who is passionate about building robust,
scalable, and high-performance data systems. The ideal candidatewill have deep expertise in SQL, Python, AWS, and Databricks, with a proven track record of designing and implementing modern data pipelines and analytical frameworks.
Key Responsibilities
- Design, develop, and maintainscalable data pipelines and ETL processes for data ingestion, transformation, and storage.
- Work with cross-functional teams to defineand deliver data solutions supporting business and analytics needs.
- Optimize and fine-tune SQL queries, data models, and pipeline performance.
- Build and manage data workflows in Databricks and integrate with AWS data services (S3, Redshift, Glue, Lambda, etc.).
- Ensure data accuracy, consistency, and reliability throughdata quality checksand monitoring frameworks.
- Collaborate with Data Scientists, Analysts, and Productteams to enableself-service analytics and advanced data-driven insights.
- Follow best practices for data governance, security, and compliance.
- Continuously evaluateemerging data technologies and propose innovative solutions for process improvement.
Required Skills & Qualifications
- Bachelor's or master's degreein computer science,Information Technology, or a related field.
- Overall 5+ years of experience and hands-on experience in Data Engineering or related roles.
- Strong proficiency in SQL for complexquery development and data manipulation.
- Expertise in Python for building data processing and automation scripts.
- Experience with AWS ecosystem especially S3, Glue, Redshift, Lambda, and EMR.
- Hands-on experience with Databricks for data processing, transformation, and analytics.
- Experience workingwith structured and unstructured datasetsin large-scale environments.
- Solid understanding of ETL frameworks, data modeling, and data warehousing concepts.
- Excellent problem-solving, debugging, and communication skills.
Good to Have
- Experience with Airflow, Snowflake, or Kafka.
- Knowledge of CI/CD pipelines and Infrastructure as Code (IaC) tools such as Terraformor CloudFormation.
- Exposure to data governance, metadata management, and data cataloguing tools.
