Capgemini is hiring a Data Engineer on a contract basis in Hanover, NH (onsite). In this role, you’ll design and support enterprise data solutions, build scalable ETL/ELT pipelines, and enable reliable conversion and operational analytics across Salesforce and related partner systems.
What you’ll deliver
- Design, build, test, and support scalable ETL/ELT pipelines for data conversion and future Connected onboarding analytics activities.
- Develop reusable source-to-target transformation utilities, including data cleansing, validation, reconciliation, exception handling, and controlled data loads.
- Create data utilities and curated datasets that can be consumed by Connected and related capabilities.
- Write, optimize, and maintain advanced SQL and Python code across enterprise data platforms.
- Support conversion rehearsals, cutover, hypercare, defect analysis, and post-production reconciliation.
How you’ll work with Salesforce and reporting teams
- Analyze Salesforce object data, including schema, relationships, record lifecycle, and data dependencies to support conversion, reporting, and production issue analysis.
- Partner with Salesforce Administrators and Product Owners to build advanced Salesforce reports and custom report types for operational and leadership metrics.
- Trace failures across Standard/Custom objects and processes using Salesforce data knowledge.
- Assess downstream impact of data and schema changes, then translate findings into data requirements, controls, and reporting solutions.
- Identify root causes and business impact by analyzing recurring Salesforce data failure patterns and connecting them with Middle and Back Office data.
Dashboards, monitoring, and operational support
- Build Tableau dashboards, scorecards, and analytical datasets for IS leadership and business stakeholders.
- Develop proactive alerts, monitoring reports, data-quality controls, reconciliation views, and exception reporting.
- Quantify impacted records, users, transactions, customers, and business processes to support defect triage and data-driven prioritization.
- Monitor pipeline and data-product performance, troubleshoot production issues, and support data-delivery service levels.
Engineering practices and data platform ownership
- Partner with architects, Product Owners, IS teams, business analysts, data teams, integration teams, Salesforce Administrators, and reporting teams to deliver end-to-end solutions.
- Develop and support cloud data warehouse and data lake solutions using dimensional modeling and data warehousing best practices.
- Perform code reviews and contribute to CI/CD, version control, testing, deployment, documentation, and engineering standards.
- Ensure solutions comply with enterprise data governance, security, privacy, lineage, and quality standards.
- Participate in Agile delivery and continuous improvement; mentor junior team members as appropriate.
What you bring
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field, or an equivalent education/experience combination.
- 5+ years designing and developing enterprise data solutions, including production ETL/ELT pipelines and large-scale data integration.
- Hands-on experience with Salesforce data, including standard/custom objects, relationships, data extraction, reporting, and schema-level analysis.
- Strong SQL development, data analysis, and query optimization skills.
- Experience with Snowflake or a comparable modern cloud data platform.
- Experience with Matillion or similar cloud-based integration and ELT technologies.
- Experience with Python (or another modern programming language) for automation, data processing, and reconciliation.
- Experience building operational reports, analytical datasets, dashboards, monitoring, or alerting solutions.
- Experience partnering directly with Product, application, technical, and business stakeholders in an Agile delivery environment.
Bonus alignment (preferred)
- Experience supporting Salesforce-based enterprise applications, data migrations, conversions, or production operations.
- Experience creating advanced Salesforce reports and collaborating on custom report types.
- Experience with Tableau dashboard development and leadership reporting.
- Experience integrating Salesforce data with Middle Office, Back Office, ERP, finance, onboarding, or operational platforms.
- Knowledge of Salesforce APIs, Bulk API, data-loader patterns, change-data-capture concepts, or enterprise integration patterns.
- Experience implementing automated data-quality checks, reconciliation frameworks, proactive monitoring, and alerting.
- Familiarity with enterprise data governance practices and cloud data services; AI/ML data engineering concepts are a plus.
- Foundational knowledge of Salesforce Data Cloud concepts (ingestion, harmonization, identity resolution, activation).
Compensation and benefits
$48–$75 per hour (USD). Benefits include medical, dental, vision, and retirement benefits.
Tools and technical focus
Snowflake, Salesforce, SQL, APIs, ETL/ELT, DevOps & CI/CD, data validation, Matillion, Tableau, Python, data warehousing, data lakes, dimensional modeling, Git.
