Capgemini

Lead Data Engineer - Databricks

Capgemini$103K — $128K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data engineering and large-scale data integration
  • Expertise with Databricks Native Data Loader, Delta Lake, and enterprise data migration
  • Strong knowledge of ETL/ELT processes and data pipeline architecture
  • Hands-on experience with cloud-based data platforms (Azure, AWS, etc.)
  • Ability to mentor and lead engineering teams in technical practices

Responsibilities

  • Design and implement enterprise-scale data ingestion frameworks
  • Optimize batch and streaming data pipelines from multiple data sources
  • Develop robust ELT/ETL pipelines using Databricks and Spark
  • Lead architectural decisions on data storage and processing frameworks
  • Create scalable data pipelines to transform unstructured data into analytics-ready datasets

Benefits

  • Paid time off including vacation, personal days, and sick leave
  • Comprehensive medical, dental, and vision coverage
  • Retirement savings plans, such as 401(k)
  • Life and disability insurance
  • Employee assistance programs
Full Job Description
Job Location

Job is located in NY - Onsite Hybrid

Your Role

Role Overview

We are seeking a highly skilled Lead Data Engineer to design, develop, and optimize scalable data ingestion and processing solutions using Databricks native capabilities. The ideal candidate will possess deep expertise in data engineering, large-scale data integration, and cloud-based data platforms, with hands-on experience in Databricks Native Data Loader, Lakeflow Connect, Delta Lake, and enterprise data migration from relational databases such as Oracle, MySQL, and SQL Server.

This role will lead the design and implementation of modern data pipelines, mentor engineering teams, and collaborate closely with business and technology stakeholders to deliver reliable, scalable, and high-performing data solutions.

Key Responsibilities

Databricks Data Engineering & Data Ingestion
Design and implement enterprise-scale data ingestion frameworks using Databricks Native Data Loader, Lakeflow Connect, and other Databricks-native capabilities.
Build and optimize batch and streaming data pipelines for ingesting data from Oracle, MySQL, SQL Server, APIs, and other enterprise data sources.
Develop robust ELT/ETL pipelines leveraging Databricks, Spark, Delta Lake, and cloud-native technologies.
Implement end-to-end data movement, transformation, validation, and monitoring solutions.
Lead architectural decisions related to data ingestion, storage, processing, and governance.

Data Engineering
Create and maintain optimal data pipeline architecture.
Build scalable data pipelines that transform raw and unstructured data into analytics-ready datasets.
Assemble large, complex datasets that meet both functional and non-functional business requirements.
Identify, design, and implement process improvements, including automation, infrastructure optimization, and scalability enhancements.
Develop infrastructure for extraction, transformation, and delivery of data from diverse data sources using distributed processing technologies.
Build and maintain new integrations required for optimal data extraction, transformation, and loading (ETL/ELT).
Implement processes to validate data and monitor data quality, ensuring production data is accurate and reliable.
Perform root cause analysis on data issues and recommend corrective actions.
Write unit and integration tests, adopt Test-Driven Development (TDD) practices, and maintain technical documentation.
Ensure platform reliability, performance optimization, and adherence to enterprise standards.

Leadership & Collaboration
Provide technical leadership and mentoring to junior engineers.
Collaborate with Product, Engineering, Analytics, Architecture, and Business stakeholders to understand requirements and deliver data solutions.
Drive best practices in coding, DevOps, CI/CD, testing, and documentation.
Participate in architecture reviews, code reviews, and technical design discussions.
Support Agile development processes and contribute to sprint planning and estimation activities.'

The base compensation range for this role in the posted location is: 103330 to 128656

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

About Capgemini

Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The company is headquartered in Paris, France and operates in over 50 countries. Capgemini provides a range of services including strategy and transformation, application services, technology services, and engineering services. The company serves clients in a variety of industries including automotive, consumer products, financial services, healthcare, and retail.
Learn more about Capgemini
Industry
Founded
1967
NASDAQ

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