Lead Data Engineer

The Lead Data Engineer is responsible for architecting, building, and operationalizing data pipelines that support enterprise data and analytics initiatives.

This role leads the development and optimization of data pipelines, ensures high data quality, mentors team members, and partners with cross-functional stakeholders to deliver curated, reliable, and scalable datasets for business and analytical use cases.

The Lead Data Engineer also contributes to data governance, strategic planning, and the adoption of modern data engineering tools and standards across the organization.

• Architect, build, and maintain scalable, production-grade data pipelines.
• Support the modernization of data management infrastructure with a strong focus on automation and efficiency.
• Collaborate with data scientists, business analysts, and other stakeholders to refine data requirements for analytics use cases.
• Train and mentor team members on data pipelining, preparation techniques, and best practices.
• Work with data governance teams to validate and promote curated content into enterprise data catalogs.
• Ensure data quality by validating accuracy, completeness, consistency, and conformance to business rules.
• Communicate complex data engineering concepts to both technical and non-technical audiences.
• Enable stakeholders by ensuring data solutions meet business needs and provide actionable insights.
• Provide leadership, coaching, and direction to team members while fostering cross-functional collaboration.
• Analyze emerging technologies and assess impact on data architecture and engineering practices.
• Serve as a role model for change adoption and continuous improvement.
• Perform additional duties as assigned.

• Bachelor’s degree in Computer Science, Statistics, or a related field.
• 7+ years of experience in data management disciplines (data integration, modeling, optimization, data quality, etc.).
• 7+ years of experience with database programming languages and advanced analytics.
• Demonstrated experience building and optimizing data pipelines and data integration frameworks.
• Strong ability to lead teams, mentor technical talent, and coordinate cross-functional efforts.
• Ability to communicate complex technical concepts clearly to diverse stakeholders.

• Master’s degree in Computer Science, Statistics, or related field.
• Experience with AWS data engineering tools such as Glue, Lambda, Athena, etc.
• Experience with BI and data visualization tools.
• Experience with both open-source and commercial data science platforms.
• Experience with Agile methodologies.
• Strong knowledge of modern data management architectures and processes.
• Expertise in building, managing, and optimizing large-scale data pipelines.
• Experience with Dev Ops capabilities such as version control, automated builds, testing, and release management.
• Ability to mentor junior team members and lead cross-functional teams.
• Experience in financial services is a plus.
• Willingness to learn new technologies and adapt to evolving environments.