Senior Data Engineer

Senior Data Engineer

Anywhere

Type: Permanent

Category: Data

Industry: Technology

Workplace Type: Remote

Standard

Hours:

Open

Reference : JN -

Date Posted: 10/20/2026

Shortcut:

Description:

Remote

Our client seeks a Senior Data Engineer to own the governed transformation layer end-to-end. The role will design and build Snowflake transformation layers, migrate legacy SQL views and user-maintained dimensions into versioned, tested dbt models with lineage, and define conformed dimensions and operational facts to unify multi-ERP environments. The position will establish modeling, testing, naming, documentation, and CI/CD standards. The work is hands-on with dbt, SQL, and Python.

This is a full-time, permanent opportunity, offering a competitive salary and comprehensive benefits package. Qualified applicants must be willing and able to work on a w2 basis.

Salary: $101,000 - $161,800/ yr. w2

JN -

• Design and build the Snowflake transformation layer from raw to staging to conformed to marts as the governed foundation for reporting and AI/ML.
• Migrate existing SQL views to versioned, tested dbt models with full lineage.
• Define conformed dimensions and operational facts across multi-ERP environments using Kimball principles including star schemas, surrogate keys, fact grain, and SCD Type 1 and Type 2.
• Set standards for modeling, testing, naming, documentation, CI/CD, Git workflows, code review, dbt project structure, model contracts, and release management.
• Partner with report owners to validate semantic equivalence and minimize disruption during BI cutovers.
• Define and own the semantic layer across Snowflake, dbt, and Power BI to ensure consistent metrics.
• Implement data quality testing, observability, and lineage with dbt tests and equivalent tools, partnering with IT Audit on SOX-relevant controls.
• Design models for AI/ML and agent readiness with stable keys, clear semantics, and metadata for LLM retrieval and tool use.
• Collaborate with AI/analytics teams on feature-table patterns, golden-record exposure, and data foundations for agentic applications.

• 7+ years in data or analytics engineering with 4+ years on a cloud data warehouse, preferably Snowflake.
• Expert SQL including window functions, performance tuning, and incremental load patterns.
• 3+ years of production dbt experience, including macros, tests, snapshots, incremental strategies, exposures, and documentation. Experience designing and maintaining a dbt project from scratch.
• Hands‑on Kimball dimensional modeling with star schemas, conformed dimensions, surrogate keys, and SCD Type 1 and Type 2.
• Production experience with at least one ingestion tool such as Fivetran, Airbyte, Informatica, or Matillion and one orchestrator such as dbt Cloud, Airflow, Dagster, or Azure Data Factory.
• Hands‑on Git and CI/CD for data using Git Hub Actions, Azure Dev Ops Pipelines, or Git Lab CI with code review and release practices.
• Proficient Python for data tooling including dbt macros, automation, data quality frameworks, and lightweight APIs.
• Experience modeling data from at least one enterprise ERP such as Oracle, SAP S/4
  
  HANA, SAP ECC, or Microsoft Dynamics.
• Strong written communication for standards, runbooks, and documentation.
• Self‑starter effective in a fast‑paced multi‑ERP environment with minimal supervision.
• Experience supporting AI/ML, RAG, or agentic workloads from a warehouse layer.
• Preferred:
  Table‑level experience with SAP ECC or S/4
  
  HANA finance and logistics tables, Power BI semantic models and DAX, regulated industry background, SOX ITGC familiarity, and exposure to MDM tooling.

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related quantitative field. Equivalent…