Data Engineer

Capgemini; Hanover (NH); On-site; USD 68,000 - 105,000; Full time

Benefits offered by this job

Medical benefits

Retirement benefits

Job summary

The Data Engineer at Tundra Technical Solutions designs, develops, and supports enterprise data solutions for data conversion, operational analytics, and production monitoring.

This role emphasizes Salesforce data model knowledge and collaboration with Product Owners, IS teams, architects, Salesforce administrators, and business stakeholders to deliver reliable conversion pipelines, reusable data utilities, leadership reporting, Tableau dashboards, and proactive insights across Salesforce and

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
• 5+ years of experience designing and developing enterprise data solutions, including production ETL/ELT pipelines and large-scale data integration.
• Hands-on experience with Salesforce data, including standard and custom objects, relationships, and reporting.
• Strong SQL development, data analysis, and query optimization skills.
• Experience with Snowflake or a comparable cloud data platform.
• Experience with Matillion or similar ELT tools.
• Experience with Python or another modern programming language for automation and data processing.

Responsibilities

• Design, build, test, and support scalable ETL/ELT pipelines for data conversion and analytics.
• Develop reusable utilities for data transformation, cleansing, validation, reconciliation, and controlled loads.
• Create data utilities and curated datasets for Connected and related capabilities.
• Write, optimize, and maintain SQL, Python code across enterprise data platforms.
• Support conversion rehearsals, cutover, hypercare, defect analysis, and post-production reconciliation.
• Analyze Salesforce object data, schema, and dependencies to support conversion and reporting.
• Build Tableau dashboards and leadership reports; establish monitoring and data-quality controls.

Skills

SQL

Python

ETL/ELT

Data Warehousing

Tableau

Salesforce data

Data quality

Education

Bachelor's degree in CS/IS/Engineering

Tools

Snowflake

Matillion

dbt

Tableau

Job description

The Data Engineer designs, develops, and supports enterprise data solutions for data conversion, operational analytics, and production monitoring.

The role combines core enterprise data engineering expertise with hands‑on knowledge of the Salesforce data model and a foundational understanding of Salesforce schema, objects, relationships, and reporting.

This position partners closely with Application Product Owners, IS teams, architects, Salesforce administrators, and business stakeholders to deliver reliable conversion pipelines, reusable data utilities, leadership reporting, Tableau dashboards, and proactive insights across Salesforce and partner systems (Middle and Back Office).

Essential Functions:

Design, build, test, and support scalable ETL/ELT pipelines for data conversion and future Connected - onboarding systems analytics activities.

Develop reusable utilities for source-to-target transformation, 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, Python, and data-processing code across enterprise data platforms.

Support conversion rehearsals, cutover, hypercare, defect analysis, and post-production reconciliation.

Salesforce Data Engineering & Reporting:

Analyze Salesforce object data, schema, relationships, record lifecycle, and data dependencies to support conversion, reporting, and production issue analysis.

Work with Salesforce Administrators and Product Owners to build advanced Salesforce reports and custom report types that support operational and leadership metrics.

Use Salesforce data knowledge to trace failures across various Standard/Custom objects and processes.

Assess the downstream impact of data and schema changes and translate findings into data requirements, controls, and reporting solutions.

Operational Analytics, Monitoring & Insights:

Analyze recurring data failure patterns in Salesforce and connect them with Middle and Back Office data to identify root causes, trends, and business impact.

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.

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.

Conduct 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, technical design, continuous improvement, and knowledge-sharing activities; mentor junior team members as appropriate.

Minimum Education and Experience:

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related field, or an equivalent combination of education and experience.

5+ years of experience designing and developing enterprise data solutions, including production ETL/ELT pipelines and large‑scale data integration.

Hands‑on experience working with Salesforce data, including standard and custom objects, object 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.

Preferred Qualifications:

Experience supporting Salesforce‑based enterprise applications, data migrations, conversions, or production operations.

Experience creating advanced Salesforce reports and collaborating with Salesforce Administrators on custom report types.

Experience with Tableau dashboard development, data‑source design, and leadership reporting.

Experience integrating Salesforce data with Middle Office, Back Office, ERP, finance, onboarding, or operational platforms.

Experience with Snowflake architecture and performance tuning; Matillion, dbt, Informatica, or comparable ELT 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 cloud data services, AI/ML data engineering concepts, and enterprise data governance practices.

Foundational knowledge of Salesforce Data Cloud, including data ingestion, harmonization, identity resolution, and data activation concepts.

Technical Skills:

Salesforce data model, schema, objects, relationships, reporting, and data extraction

Snowflake and advanced SQL development / optimization

Matillion or comparable ETL/ELT tools

Python and data automation

Tableau and analytical data‑source design

Data warehousing, data lakes, and dimensional modeling

Data integration, APIs, and batch‑processing patterns

Data conversion, migration, reconciliation, validation, and exception handling

Production monitoring, alerting, and root‑cause analysis

CI/CD, Git, testing, and DevOps practices

Data quality, lineage, governance, security, and privacy

Core Competencies:

Critical thinking and structured problem solving

Clear communication with technical and business audiences

Cross‑functional relationship building

Accountability and ownership

Results orientation and delivery discipline

Ability to manage complexity and ambiguity

Situational adaptability and continuous improvement mindset

The pay range that the employer in good faith reasonably expects to pay for this position is $48.54/hour - $75.85/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.