Job Role: Senior Data Engineer
Location: Hyderabad
Experience Required: 4-8 years
Job Type: Full-Time
No of Positions: 01
We are looking for a
Senior AWS Data Engineer to lead the design, development, and maintenance of scalable
cloud-based data lakes, data warehouses, and analytics platforms. The ideal candidate will bring strong hands-on experience in AWS data services, ETL engineering, and data modeling, while collaborating closely with architects, analysts, DevOps teams, and business stakeholders.
This role requires strong ownership, problem-solving mindset, and the ability to work in complex, cross-functional environmentspreferably with exposure to
Healthcare, Life Sciences, Genomics, Clinical/Pre-clinical data domains.
Key Responsibilities
- Design, build, and optimize end-to-end data pipelines and ETL/ELT workflows on AWS.
- Lead development and maintenance of data lakes and enterprise data warehouses, supporting analytical and operational workloads.
- Implement scalable ingestion and integration frameworks for structured and semi-structured data from multiple sources.
- Develop and manage data processing pipelines using AWS Glue (PySpark), SQL, and Python frameworks.
- Own and improve data modeling and data warehouse design (dimensional models, star/snowflake schema).
- Ensure robust data quality checks, validation frameworks, monitoring, alerting, and logging for production reliability.
- Collaborate with cloud/platform/DevOps teams to implement CI/CD automation and Infrastructure-as-Code best practices where applicable.
- Implement and enforce data governance, security, and compliance across the AWS data ecosystem.
- Perform performance tuning and cost optimization across services like Redshift, Athena, Glue, and S3.
- Mentor junior engineers, conduct code reviews, enforce best practices, and contribute to technical standards.
Required Skills & Qualifications
AWS Data Services
- Strong hands-on experience with:
- Amazon S3, AWS Glue, Lake Formation, Redshift, Athena, Lambda
- Experience with Redshift Spectrum and partitioned querying best practices.
ETL / Data Engineering
- Strong ETL development experience using:
- AWS Glue (PySpark), Python, and SQL
- Experience working with:
- CSV, JSON, Parquet, and API-based data ingestion
- Batch and near-real-time ingestion patterns
Data Modeling & Warehousing
- Strong expertise in:
- Dimensional modeling
- Star and snowflake schema design
- Designing scalable and maintainable datasets for BI/analytics use
Data Governance & Data Quality (Must Have)
- Proven experience implementing:
- Data quality frameworks and automated validation checks
- Metadata management, lineage, and governance concepts
- Access controls and policy-driven governance (Lake Formation preferred)
DevOps & Engineering Practices
- Hands-on experience with:
- GitHub
- CodeBuild / CodePipeline
- CI/CD practices for data workflows
Security
- Strong understanding of:
- IAM, KMS, encryption, secure access patterns
- AWS cloud security best practices
Preferred Qualifications
- Bachelor's/Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
- 48 years of experience in Data Engineering / Cloud Data Platforms.
- Exposure to Healthcare / Life Sciences / Pharma datasets and environments.
- Familiarity with compliance frameworks such as:
- GxP, HIPAA (good to have)
- Experience with visualization and analytics tools:
- QuickSight (optional)
- AWS Certifications (Good to have):
- AWS Certified Data Analytics Specialty
- AWS Certified Developer Associate
- AWS Certified Solutions Architect Associate
