
Consultant, Data Engineer
McLean, VA · HybridJob$75–120K/yrSeen 1w agoSeen in employer's feed 3 days ago
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At a glance
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Job overview
The Consultant, Data Engineer builds and maintains Databricks data pipelines for Infinitive clients, moving data from source systems into tables used by analysts and data scientists. The role works on project teams with senior engineers, architects, and business analysts, and includes client-facing work and exposure to new data platforms and industries. The position is hybrid and requires on-site work with clients in McLean, Virginia.
Skills & qualifications
Skills
Qualifications
Full job description
**This is a hybrid role and requires work on-site with our clients.
About Infinitive:
Infinitive is a data and AI consultancy that enables its clients to modernize, monetize and operationalize their data to create lasting and substantial value. We possess deep industry and technology expertise to drive and sustain adoption of new capabilities. We match our people and personalities to our clients' culture while bringing the right mix of talent and skills to enable high return on investment.
Infinitive has been named “Best Small Firms to Work For” by Consulting Magazine 9 times most recently in 2026. Infinitive has also been named a Washington Post “Top Workplace”, Washington Business Journal “Best Places to Work”, and Virginia Business “Best Places to Work.”
About the role As a Consultant, Data Engineer, you will build and maintain data pipelines on Databricks for Infinitive clients. You will work on project teams with senior engineers, architects and business analysts, writing production Python, PySpark and SQL code that moves data from source systems into tables the client's analysts and data scientists use every day. The role is ideal for an engineer with one to three years of experience who wants client-facing work and regular exposure to new data platforms and industries. The client location is McLean, Virginia. What you will do
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Build and maintain batch and incremental ETL pipelines in Databricks using Python, PySpark and Spark SQL.
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Ingest data from relational databases, APIs, flat files and cloud storage (Amazon S3, Azure Data Lake Storage) into Delta Lake tables.
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Implement bronze, silver and gold layers following medallion architecture patterns.
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Write and tune SQL for transformations, data validation and reporting tables.
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Add data quality checks, handle schema changes and troubleshoot failed jobs.
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Schedule and monitor workloads with Databricks Workflows, working within Unity Catalog permissions.
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Tune Spark jobs for performance and cost, including partitioning, file sizing and cluster configuration.
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Use Git for version control, take part in code reviews and contribute to CI/CD pipelines.
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Document pipelines, source-to-target mappings and runbooks so client teams can run what you build.
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Join client meetings to clarify requirements, report status and walk through your work.
What you bring
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1 to 3 years of professional experience in data engineering, software engineering or a related technical role.
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Bachelor's degree in computer science, information systems, engineering, mathematics or a related field, or equivalent experience.
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Hands-on experience with Databricks on a professional or substantial academic project.
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Working proficiency in Python for data processing.
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Experience building transformations with Apache Spark and PySpark (DataFrames and Spark SQL).
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Strong SQL, including joins, window functions, CTEs and aggregations.
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Understanding of ETL concepts such as incremental loads, slowly changing dimensions, dimensional modeling and data quality checks.
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Familiarity with at least one cloud platform (AWS, Azure or Google Cloud).
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Clear written and verbal communication, and comfort explaining technical work to non-technical stakeholders.
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Authorization to work in the United States [confirm sponsorship policy].
Nice to have
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Databricks Certified Data Engineer Associate certification.
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Experience with Delta Lake features such as MERGE and time travel, or with Lakeflow Declarative Pipelines (formerly Delta Live Tables).
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Exposure to Unity Catalog, dbt, Apache Airflow or Azure Data Factory.
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Experience with Terraform or CI/CD tools such as GitHub Actions or Azure DevOps.
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Prior consulting or client-facing experience.
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Background in financial services, healthcare or media data.
Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $75,000 - $120,000.00.
Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.
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How this job compares
Set against the 5,720 open Data Engineer jobs on Olive Jobs, counted October 27, 2026.
- Pay
- This posting$75–120K/yr
- Virginia median$116–190K/yr308 salary ranges
- US median$127–208K/yr4,350 salary ranges
This range's midpoint, $98K, is 38% below the Virginia median midpoint ($157K) — in the lowest quarter of Data Engineer salary ranges in Virginia.
- Openings
- Olive Jobs lists 383 open Data Engineer jobs in Virginia and 5,720 across the US. 8% of them nationwide are listed as remote or flexible.
- Hiring the most in Virginia
- Deloitte95 open
- Capital One29 open
- Accenture26 open
- Experience
- This posting asks for at least 1 year of experience — less than three in four Data Engineer postings that state a minimum ask for (median 5 years, across 4,958 postings).
- Education
- 2,660 of the 5,720 open Data Engineer jobs (47%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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