About the Role :

We are looking for a highly skilled Manager / Lead Data Engineering & ETL Operations to drive enterprise-scale data integration, cloud transformation, and analytics initiatives. This role requires a strong blend of hands-on technical expertise and leadership capability, making it ideal for professionals transitioning from Senior Engineer to Manager.

The ideal candidate will have deep expertise in ETL development, cloud platforms, data warehousing, and large-scale data processing, along with experience leading teams, managing delivery, and solving complex data challenges within pharma/life sciences environments.

This role offers an exciting opportunity to work on modern data ecosystems, scalable cloud architectures, and high-impact analytics platforms.

Key Responsibilities :

- Lead ETL development, operations, and production support activities.

- Design, develop, and manage cloud-based data platforms using AWS, Azure, or GCP.

- Build and optimize enterprise data warehouse solutions using Snowflake and/or Redshift.

- Develop and maintain scalable data pipelines using SSIS, Matillion, SnapLogic, and PySpark.

- Implement dimensional data models including Slowly Changing Dimensions (SCD Type 1, Type 2, and Type 3).

- Ensure data quality, scalability, reliability, and performance optimization across data platforms.

- Support downstream analytics and reporting initiatives using Tableau and/or Power BI.

- Lead small-to-medium engineering teams, conduct code reviews, and mentor team members.

- Collaborate closely with business, analytics, and cross-functional stakeholders to deliver high-quality data solutions.

- Drive root-cause analysis, issue resolution, and continuous improvement for production data systems.

- Participate in both hands-on individual contributor responsibilities and leadership activities.

Required Skills & Experience

Mandatory Requirements

- 7+ years of experience in Data Engineering / ETL development.

- Minimum 3+ years of experience in pharma, healthcare, or life sciences domain.

- Strong expertise in ETL tools such as SSIS, Matillion, and SnapLogic.

- Hands-on experience with cloud platforms including AWS, Azure, or GCP.

- Strong experience working with modern data warehouses such as Snowflake and/or Redshift.

- Excellent understanding of data warehousing concepts and dimensional modeling techniques including SCD Type 1/2/3.

- Strong hands-on experience with PySpark for large-scale data processing.

- Proven experience ensuring data quality, scalability, reliability, and performance optimization of data pipelines.

- Minimum 2+ years of experience leading teams, mentoring engineers, and managing end-to-end delivery.

- Experience working with business stakeholders and solving complex data-related challenges.

- Prior experience in health/pharma/life sciences companies or consulting/service organizations with strong pharma analytics exposure.

Preferred Skills

- Experience with Tableau and/or Power BI.

- Exposure to production support and data operations environments.

- Strong stakeholder communication and problem-solving abilities.

- Ability to balance hands-on technical work with team leadership responsibilities.

Why Join Us?

- Opportunity to lead enterprise-scale cloud and data transformation initiatives.

- Exposure to cutting-edge data engineering and analytics ecosystems.

- High-impact role with equal focus on leadership and hands-on engineering.

- Collaborative and innovation-driven work environment.

- Hybrid work flexibility with 6 days/month work-from-home option.

Additional Information :

- Work Mode : Hybrid

- WFH Flexibility : 6 days/month

- Compensation : CTC includes 10% variable pay

- Role Structure : Equal mix of Individual Contributor and Leadership responsibilities