Databricks Data Engineer - Mc Lean - Capgemini Government Solutions

    Capgemini Government Solutions
    Description

    Capgemini Government Solutions is seeking an experienced Databricks Data Engineer to lead the migration of existing Pentaho (Kettle) ETL workflows to a modern Databricks-based ETL architecture, with downstream data loads into Salesforce. This role requires strong hands-on engineering skills, migration experience, and the ability to translate legacy ETL logic into scalable, cloud-native data pipelines.

    Is this the role you are looking for If so read on for more details, and make sure to apply today.

    The ideal candidate is comfortable working independently, partnering with stakeholders, and delivering production-ready pipelines in a secure and governed environment.

    Job Responsibilities:

    •  Analyze and reverse-engineer existing Pentaho ETL jobs and transformations
    • Design and implement Databricks ETL pipelines using:
      • Apache Spark (PySpark / Spark SQL)
      • Databricks Workflows / Jobs
      • Delta Lake
    • Re-platform ETL logic including:
      • Data extraction from relational sources (PostgreSQL, SQL Server, etc.)
      • File-based ingestion (CSV, ZIP, SFTP workflows)
      • Transformations, validations, and enrichment
    • Implement data loading strategies into Salesforce, including:
      • Salesforce APIs (Bulk API, REST API)
      • Handling large volumes, retries, and error handling
      • Incremental vs full loads
    • Optimize pipelines for performance, scalability, and cost
    • Implement logging, monitoring, and data quality checks
    • Support testing, validation, and parallel runs during migration
    • Produce technical documentation for migrated pipelines
    • Collaborate with architects, platform teams, and business stakeholders

    Required Qualifications:

    • U.S. Citizenship is required.
    • Eligible to obtain and maintain Government Security Clearance.
    • 5+ years of experience in data engineering / ETL development
    • Strong hands-on experience with Databricks
    • Proficiency in PySpark and Spark SQL
    • Prior experience migrating from legacy ETL tools (Pentaho, Informatica, Talend, SSIS, etc.)
    • Experience integrating with Salesforce as a target system
    • Solid understanding of:
      • ETL/ELT design patterns
      • Data modeling and transformation logic
      • Error handling and restartability
    • Experience working with relational databases
    • Strong troubleshooting and problem-solving skills

    Preferred Qualifications:

    • Direct experience migrating Pentaho (Kettle) to Databricks
    • Experience with Salesforce data models (objects, relationships, limits)
    • Familiarity with:
      • CI/CD for data pipelines
      • Git-based source control
      • Cloud platforms (AWS preferred)
    • Experience in regulated or compliance-driven environments (FedRAMP, HIPAA, etc.)
    • Knowledge of data governance, lineage, and auditability

    About Capgemini

    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. The Group reported 2024 global revenues of €22.1 billion.

    Get the future you want |

    Disclaimer

    All qualified applicants will be considered for employment based on their skills, and merit.

    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.

    Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.

    Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is 150k-170k.

    This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. xhuatnn

    Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.


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Databricks data engineer