Data Engineer at Capgemini Portugal

Nashville, Tennessee, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Jun, 26

Salary

100000.0

Posted On

23 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Google Cloud Platform, GCP, PySpark, Delta Lake, Spark Streaming, BigQuery, Cloud Storage, Dataflow, Cloud Composer, Vertex AI, Data Modeling, Python, SQL, CI/CD, Terraform

Industry

IT Services and IT Consulting

Description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.Job Description . We are seeking a skilled Data Engineer with hands-on experience in Databricks and Google Cloud Platform (GCP) to design, build, and optimize data pipelines and analytics solutions. The ideal candidate will have a strong background in distributed data processing, cloud architecture, and data modeling. This role partners closely with data analysts, data scientists, and business stakeholders to deliver scalable, reliable, and high‑quality data products. Your role Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake). Optimize pipelines for performance, cost efficiency, and scalability within GCP. Develop batch and streaming data processes using Spark Streaming, and related technologies. Implement data solutions leveraging GCP services such as BigQuery, Cloud Storage, Dataflow, Cloud Composer, and Vertex AI integrations. Apply best practices for cloud security, IAM configuration, monitoring, and cost management. Build and maintain data models, including dimensional modeling and data vault structures. Implement data quality frameworks, validation rules, and automated testing. Manage data versioning, governance, and lineage using tools such as Unity Catalog or GCP Data Catalog. Partner with cross‑functional teams to gather requirements and translate them into technical designs. Provide technical guidance and influence engineering best practices across the team. Contribute to documentation, architectural diagrams, and knowledge sharing.Skills and Expereince 3+ years of experience as a Data Engineer or similar role. Strong hands-on experience with Databricks, including: PySpark/Spark Delta Lake Databricks workflows/jobs Proficiency with GCP: BigQuery Cloud Storage Dataflow or Dataproc Strong coding skills in Python and SQL. Solid understanding of distributed systems, data warehousing, and data architecture principles. Experience with CI/CD tools (GitHub, GitLab, Azure DevOps, or similar). Preferred Qualifications Databricks or GCP certifications (e.g., Data Engineer, Architect). Experience with Terraform or other Infrastructure-as-Code tools. Knowledge of ML workflows or MLOps frameworks. Familiarity with data governance tools (Unity Catalog, Great Expectations, dbt, etc.). The base compensation range for this role in the posted location is 70,000- 100,000 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. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Responsibilities

The Data Engineer will be responsible for designing, building, and maintaining ETL/ELT pipelines using Databricks (PySpark, Delta Lake) and optimizing these solutions within the Google Cloud Platform environment. This role involves developing batch and streaming data processes while implementing data quality frameworks and ensuring adherence to cloud security best practices.