Lead Data Engineer

Key Responsibilities:

Technical Leadership & Architecture

• Strong hands-on experience with Snowflake and cloud data platforms, including data warehouse design, data modeling, performance optimization, ETL/ELT pipelines, and integration with enterprise data platforms across AWS, Azure, or Google Cloud Platform.
• Collaborate with Data Architects, Enterprise Architects, and Technology teams on solution design, integration patterns, and technical standards.
• Translate business and functional requirements into secure, scalable, and maintainable technical solutions.
• Lead design reviews, troubleshooting, and technology decision-making.
• Support data platform modernization, AI/ML, and advanced analytics initiatives from a data engineering perspective.

Stakeholder & Offshore Team Leadership

• Work with business and technology stakeholders to define priorities, requirements, and strategic initiatives, communicating technical recommendations clearly to technical and non-technical audiences.
• Translate decisions into clear direction, priorities, and context for the offshore engineering team.
• Coordinate dependencies, issue resolution, and knowledge transfer across onsite and offshore teams.
• Mentor offshore engineers on technical implementation and engineering best practices.

Delivery, Governance & Continuous Improvement

• Provide technical oversight across multiple initiatives, ensuring alignment with architecture, security, data governance, and engineering standards.
• Review deliverables for quality, performance, reliability, and maintainability.
• Support estimation, planning, prioritization, and resource planning.
• Proactively identify and manage technical risks, dependencies, and blockers.
• Drive continuous improvement in engineering processes, tools, and delivery effectiveness.

Required Skills

• 8–10 years of experience in data engineering, data integration, or related roles.
• Strong hands-on SQL and Python or another data engineering language.
• Strong experience with ETL/ELT, data pipelines, data warehousing, and data modeling.
• Strong hands-on experience with Snowflake and cloud data platforms on AWS, Azure, or Google Cloud Platform.
• Experience with APIs, data integration technologies, and distributed data processing.
• Experience with orchestration tools such as Apache Airflow.
• Experience with Git, CI/CD, and DevOps practices for data engineering.
• Familiarity with data governance, security, and data quality practices.
• Experience leading distributed engineering teams in an Agile environment.

Preferred Experience

• Snowflake implementation or migration within enterprise-scale data modernization programs.
• Experience supporting AI/ML, GenAI, or advanced analytics initiatives.
• Healthcare domain experience including healthcare data, systems, workflows, and regulatory considerations, is a strong plus.