About the Role :

We are looking for a highly skilled Manager / Lead Data Engineering & ETL Operations to drive enterprise-scale data integration, data warehousing, and analytics solutions.

This is a hands-on leadership role requiring strong expertise in ETL development, cloud data platforms, and large-scale data processing, along with the ability to lead teams and deliver business-critical data solutions.

The ideal candidate will bring a blend of technical depth and leadership capabilities, with experience managing end-to-end data engineering initiatives in pharma, healthcare, or life sciences environments.

Key Responsibilities :

- Lead ETL development, production support, and data operations initiatives.

- Design, build, and optimize scalable data pipelines using ETL tools and cloud technologies.

- Develop and maintain cloud-based data platforms on AWS, Azure, or GCP.

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

- Implement dimensional data models including SCD Type 1, Type 2, and Type 3.

- Develop large-scale data processing solutions using PySpark.

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

- Support business intelligence, analytics, and reporting teams with high-quality data solutions.

- Conduct code reviews and establish engineering best practices.

- Lead, mentor, and guide a team of data engineers.

- Collaborate closely with business, analytics, and stakeholder teams to understand data requirements and deliver solutions.

- Drive root-cause analysis, troubleshooting, and resolution of complex data issues.

Required Skills & Experience :

- 7+ years of experience in Data Engineering, ETL Development, Data Warehousing, or related areas.

- Minimum 3+ years of experience working within Pharma, Healthcare, or Life Sciences domains.

- Strong hands-on experience with ETL tools such as SSIS, Matillion, or SnapLogic.

- Expertise in designing and maintaining data pipelines and data integration solutions.

- Hands-on experience with cloud platforms including AWS, Azure, or Google Cloud Platform (GCP).

- Strong experience with Snowflake, Amazon Redshift, or similar cloud data warehouse technologies.

- Deep understanding of data warehousing concepts, dimensional modeling, and SCD Type 1/2/3 implementations.

- Hands-on experience with PySpark for large-scale data processing and transformation.

- Strong understanding of data quality, governance, performance optimization, and scalability best practices.

- Experience working with production support and data operations environments.

Leadership Requirements:

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

- Experience conducting code reviews and driving engineering excellence.

- Proven ability to manage stakeholder expectations and deliver business-focused data solutions.

- Strong communication and collaboration skills.

Preferred Skills:

- Experience with Tableau, Power BI, or other BI and analytics platforms.

- Exposure to data operations, monitoring, and production support processes.

- Experience working in consulting organizations or large enterprise environments.

- Knowledge of modern cloud-native data architectures and best practices.

Ideal Candidate:

- Strong Data Engineering leader with hands-on technical expertise.

- Experienced in both individual contributor and people management responsibilities.

- Comfortable owning end-to-end delivery of complex data engineering projects.

- Proven experience working with business and analytics stakeholders.

- Background in Pharma, Life Sciences, Healthcare, or consulting organizations supporting these domains.

Additional Information:

- Hybrid work model with work-from-home flexibility available for up to 6 days per month.

- Compensation includes a 10% variable component.

- Role offers an equal mix of hands-on technical responsibilities and leadership ownership.

If you are passionate about building scalable data platforms, leading high-performing teams, and solving complex data challenges, we would love to hear from you.