Data Engineer

DataJobs; Hanover (NH); On-site; USD 137,540,000 - 214,906,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Retirement benefits

Job summary

Capgemini in Hanover, NH is seeking a Data Engineer on a contract basis onsite. You will design and support enterprise data solutions, build scalable ETL/ELT pipelines, and enable reliable conversion and analytics across Salesforce and partner systems.

You will work with Salesforce teams to create advanced reports, trace data failures, and deliver dashboards for IS leadership. Strong SQL, Python, and cloud data platform experience are required, along with collaboration in an Agile environment.

Qualifications

• 5+ years designing and developing enterprise data solutions, incl. ETL/ELT pipelines
• Hands-on experience with Salesforce data, including objects, relationships, and reporting
• Strong SQL development and data analysis skills
• Experience with modern cloud data platforms (Snowflake) and cloud ETL tools (Matillion)
• Python for automation, data processing, and reconciliation
• Experience building operational reports and dashboards in Agile environments

Responsibilities

• Design, build, test, and support scalable ETL/ELT pipelines for data conversion and onboarding analytics
• Develop reusable data transformation utilities and curated datasets
• Write, optimize, and maintain advanced SQL and Python code across data platforms
• Build Tableau dashboards and monitoring views for leadership
• Partner with Salesforce Administrators and Product Owners to improve reports and data quality

Skills

SQL

Python

Agile

Data analysis

ETL/ELT

Data integration

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or related field

Tools

Snowflake

Matillion

Tableau

Git

APIs

CI/CD

Job description

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.