Lead Data Engineer

Capgemini; Hartford (CT); Hybrid; USD 125,000 - 136,000; Full time

Benefits offered by this job

Paid time off

Medical/dental/vision

Retirement savings plans

Life and disability insurance

Employee assistance programs

Job summary

Capgemini in Hartford, CT is hiring a Lead Data Engineer in a hybrid role, requiring 3 days in the office weekly. You will build data pipelines, optimize SQL, and model data to support analytics.

You will own metadata, implement quality checks, perform performance tuning, and provide production support. Preferred certifications include SnowPro and Databricks.

This role emphasizes collaboration with stakeholders and delivery excellence in an Agile/SAFe environment.

Qualifications

• Data engineering skills and experience in building reliable data pipelines.
• Strong knowledge of database design and data modeling.
• Ability to manage stakeholders and work in Agile/SAFe environments.

Responsibilities

• Build data pipelines to support dependable data flow across systems.
• Optimize SQL for efficient querying and performance.
• Model data to enable downstream analytics and applications.
• Manage NoSQL stores as part of the data platform architecture.
• Implement quality checks to ensure data accuracy and consistency.
• Perform performance tuning across data workflows and databases.
• Own metadata management for discovery and governance.
• Provide production support to keep pipelines running.

Skills

Data Engineering

Database Engineering

Stakeholder Management

Agile/SAFe

Documentation

Delivery Excellence

Job description

Advance your data engineering career with Capgemini in Hartford, CT (hybrid), working 3 days per week in the office. This Lead Data Engineer role supports teams delivering reliable data platforms through pipeline development, performance optimization, and production-grade data practices. The estimated salary range is USD 125,000 to 136,000 per year.

What you’ll do

• Build data pipelines to support dependable data flow across systems.
• Optimize SQL for efficient querying and improved performance.
• Model data to structure information for downstream analytics and applications.
• Manage NoSQL stores as part of the data platform architecture.
• Implement quality checks to help maintain data accuracy and consistency.
• Perform performance tuning across data workflows and databases.
• Own metadata management to improve discoverability and governance of data assets.
• Provide production support to resolve issues and keep pipelines running.

What you’ll bring

• Data Engineering
• Database Engineering
• Stakeholder Management
• Agile/SAFe
• Documentation
• Delivery Excellence

Benefits and support

• Paid time off based on employee grade, including vacation (12 to 25 days), company paid holidays, personal days, and sick leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (for example, 401(k) in the U.S. or RRSP in Canada)
• Life and disability insurance
• Employee assistance programs

Preferred certifications

• SnowPro
• Databricks