Senior Consultant, Data Engineer (JDE / SAP DS)

Bizfirst; United States; Remote; USD 96,000 - 165,000; Full time

Job summary

BizFirst is seeking a Senior Consultant, Data Engineer to lead migration of legacy ETL pipelines to modern dbt and Databricks architectures. You will own end-to-end execution, collaborating with client technical stakeholders and guiding a small engineering sub-team in a hands-on contract engagement.

The role requires 5+ years in data engineering and a consulting background, with strong SQL, Python, Spark, and cloud experience.

Qualifications

• 5+ years of hands-on data engineering experience, with 2+ years in a client-facing or consulting role.
• Strong production experience with SQL, Python, Spark, dbt, and Airflow.
• Deep technical depth in Databricks and cloud environments (Azure or AWS).

Responsibilities

• Reverse-engineer legacy ETL and migrate to dbt/Databricks pipelines.
• Build automated data validation and ensure data integrity versus legacy baselines.
• Implement downstream write-back mechanisms to SQL Server for reporting continuity.
• Lead and mentor a junior team and collaborate with client stakeholders.
• Work with SAP BusinessObjects Data Services and JD Edwards ERP sources.

Skills

SQL

Python

Spark

Tools

Databricks

dbt

Airflow

Job description

Work Style/ Location: Remote, DMV area (Washington, DC, Maryland, Virginia)

Type: Contract (1099), 4.5 to 6 months, with potential conversion to full-time

Sector: Data, AI & Analytics

Target Rate: Competitive

Position Overview

BizFirst is supporting our client in identifying a Senior Consultant, Data Engineer to lead the legacy ETL reverse-engineering and pipeline migration workstream for enterprise clients. This is a hands-on contract role for a data engineer with 5+ years of experience and a consulting background.

You’ll take full technical ownership of migrating complex legacy ETL pipelines, such as SAP BusinessObjects Data Services and JD Edwards EnterpriseOne F-tables, to modern dbt and Databricks architectures, implementing automated validation and downstream write-back mechanisms.

Our client is a fast-growing global data and AI consultancy with operations across three continents and 140+ consultants serving 70+ enterprise clients. They’ve built a consultant-first culture with a proprietary learning academy, paid certifications, and deep partnerships with platforms like Snowflake, Databricks, and Google Cloud. The US office combines the credibility of an established global brand with the energy of a New York startup.

Why This Role

This is a high-ownership engagement. You’ll lead a defined migration workstream end to end, work directly with client technical stakeholders, and lead a small engineering sub-team. The engagement runs 4.5 to 6 months, with the potential to convert to a full-time role at the end.

What You'll Do

• Reverse-engineer legacy ETL. Translate legacy ETL workflows, orchestrators, and SQL Server Agent jobs into scalable dbt models and Databricks pipelines
  
• Prove data integrity. Build and execute automated data validation frameworks that compare modernized outputs against legacy data warehouse baselines
  
• Support downstream reporting. Implement transitional write-back mechanisms to SQL Server data warehouses to maintain backward compatibility for downstream reporting consumers
  
• Lead and mentor. Collaborate directly with client technical stakeholders, lead small engineering sub-teams, and mentor junior consultants
  
• Languages: SQL, Python, Spark
  
• Data Platform: Databricks
  
• Transformation & Orchestration: dbt, Airflow
  
• Cloud: Azure or AWS
  
• Legacy Sources: SAP BusinessObjects Data Services, JD Edwards EnterpriseOne F-tables, SQL Server and SQL Server Agent
  

What We're Looking For

This role leads a migration workstream hands-on, so we’re looking for proven data engineering depth and client-facing experience:

• 5+ years of hands-on data engineering experience, with 2+ years in a client-facing or consulting role
  
• Strong production experience with SQL, Python, Spark, dbt, and workflow orchestration tools such as Airflow
  
• Deep technical depth in Databricks and cloud environments (Azure or AWS)
  
• Experience migrating legacy ERP and ETL estates, such as JD Edwards or SAP
  
• Based in the DMV area (Washington, DC, Maryland, or Virginia)
  

These aren’t requirements, but if any of these describe you, we’d love to hear about it:

• Certifications: Databricks Data Engineer Professional and the like
  
• Experience with both JD Edwards EnterpriseOne and SAP BusinessObjects Data Services
  
• Contract (1099) engagement of 4.5 to 6 months
  
• Remote, for candidates based in the DMV area (Washington, DC, Maryland, and Virginia)
  
• Potential conversion to a full-time role with the client at the end of the engagement
  
• Competitive hourly rate, based on experience and fit
  
• Our client will provide any necessary hardware for contractors to conduct their work
  

Perks & Benefits (W-2 Full-Time Employees Only)

These benefits apply only to W-2 full-time employees of our client, if hired as such. For W-2 full-time employees, our client offers stock standard benefits that everybody wants, plus a few extras:

• Medical, Dental, and Vision plans picked for both young single professionals and those with families to support
  
• 401(k) match, dollar-for-dollar, up to 4% of your salary
  
• Flexible paid time off designed for adults, take time as you need it (and you do need at least two weeks off, preferably contiguous, per year)
  
• Top-of-the-line hardware, optimized for horsepower or mobility (we’re all on Macs)
  
• Proprietary learning academy with 100+ custom modules
  
• Certification stipend for the platforms you deliver on
  
• Fully remote, with colleagues who love the work and an empowerment culture that puts decisions close to the ground
  

About BizFirst

BizFirst LLC is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran status, disability, or genetic information, or any other reason prohibited by law in employment.