Lead Data Engineering Lead We are seeking a highly experienced Senior Data Engineering Lead with 8+ years of experience in modern data engineering, data warehousing, and data lake technologies across cloud platforms, including Microsoft Azure, Google Cloud Platform (GCP), and AWS. The ideal candidate will have strong technical expertise, proven leadership abilities, and experience designing scalable data solutions while collaborating with business and technical stakeholders.
Key Responsibilities Design, build, and implement scalable data pipelines using Microsoft Fabric, including Azure Data Factory, PySpark, Spark SQL, and Python. Develop and maintain ETL/ELT processes to ingest, transform, and load data from multiple sources into data warehouses, data lakes, and analytical platforms. Optimize large-scale data processing workflows to improve performance, scalability, and reliability. Implement and maintain data security, governance, and compliance standards in accordance with enterprise and regulatory requirements. Collaborate with business stakeholders, architects, and engineering teams to gather requirements and deliver effective data solutions. Lead development efforts, provide technical guidance, and ensure delivery of high-quality solutions within project timelines. Required Technical Skills Programming & Data Engineering Advanced hands-on expertise in: Python PySpark SQL Strong experience in data modeling, query optimization, and schema design. Cloud & Data Platforms Strong proficiency with Microsoft Azure Cloud Services. Experience with Microsoft Fabric and related technologies: Azure Data Factory Azure Synapse Analytics Azure Data Lake Storage Databricks Working knowledge of AWS and/or Google Cloud Platform (GCP) data services is highly desirable. Data Warehousing & Data Management Minimum 8 years of experience in modern data engineering, data warehousing, and data lake technologies.
Extensive experience with enterprise data warehouse platforms, including one or more of: Azure Synapse Analytics Azure SQL Database Snowflake Amazon Redshift Google BigQuery Strong understanding of data warehouse best practices, development standards, and methodologies. Experience with: Azure Data Lake Storage Azure Blob Storage Azure Cosmos DB Azure SQL Database ETL/ELT & Architecture Experience with ETL/ELT tools such as: Azure Data Factory (ADF) Informatica Talend Practical experience implementing Medallion Architecture and modern data lakehouse patterns.
Required Experience 8+ years of experience in data engineering, data warehousing, and cloud-based data platforms. 12+ years of experience in SQL development, schema design, and dimensional data modeling. Experience developing and optimizing big data solutions using Spark-based technologies. Strong analytical, troubleshooting, and problem-solving capabilities. Demonstrated experience leading technical teams and mentoring engineers. Preferred Qualifications Experience with Databricks (highly preferred). Experience with Azure DevOps and CI/CD implementation. Knowledge of cloud migration strategies and methodologies. 2+ years of experience with Power BI. 5+ years of experience with reporting and visualization tools such as Tableau, OBIEE, or similar platforms.
Leadership Expectations Lead and mentor data engineering teams. Drive technical design decisions and architectural standards. Manage stakeholder expectations and communicate effectively across technical and business teams. Ensure timely delivery of high-quality, scalable, and secure data solutions.
Job Description
Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.
Job Description - Grade Specific
The involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.
The base compensation range for this role in the posted location is $125,000 to $150,000
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.
