Back to jobs

Senior Data Engineer-Databricks & Data Modeling

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting

The Senior Data Engineer - Databricks & Data Modeling will develop, deploy, and maintain production data pipelines and reusable data models within Winsupply's Databricks lakehouse on Google Cloud.

Build, test, deploy, and support production ingestion and transformation pipelines using Databricks, Delta Lake, Unity Catalog, Apache Spark, Python/PySpark, and Databricks SQL.

What you’ll bring

All qualifications

Core experience

  • 7+ years of related professional experience in data engineering, data warehousing, analytics engineering, or comparable roles.
  • 3+ years of hands-on Databricks production experience with Delta Lake, Unity Catalog, Spark/PySpark, and Databricks SQL.
  • 3+ years of meaningful relational or dimensional data modeling experience, including personally designing and deploying fact/dimension or integrated business models.
  • Experience building production ETL/ELT pipelines, implementing incremental processing, and supporting operational data quality and monitoring.
  • Strong SQL and Python/PySpark skills, with hands-on Git, testing, code review, and CI/CD practices.

Preferred experience

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
  • Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles.
  • Experience integrating IBM/mainframe, DB2, distribution/supply-chain, financial, or pricing data.
Qualification wording
7+ years of related professional experience in data engineering, data warehousing, analytics engineering, or comparable roles.
3+ years of hands-on Databricks production experience with Delta Lake, Unity Catalog, Spark/PySpark, and Databricks SQL.
3+ years of meaningful relational or dimensional data modeling experience, including personally designing and deploying fact/dimension or integrated business models.
Experience building production ETL/ELT pipelines, implementing incremental processing, and supporting operational data quality and monitoring.
Strong SQL and Python/PySpark skills, with hands-on Git, testing, code review, and CI/CD practices.
Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles.
Experience integrating IBM/mainframe, DB2, distribution/supply-chain, financial, or pricing data.
Education & alternatives
Preferred Qualifications - Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline. - Databricks Certified Data Engineer Professional or comparable Databricks certification.
Apply at Winsupply

Posting record

Report an error

Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 12, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,239 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

From 13,214 similar postings that came down. Coming down is not always a hire.

Winsupply is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Databricks
  • Delta Lake
  • Spark
  • PySpark
  • GCP
Where the posting names them
Accountabilities/Responsibilities - Build, test, deploy, and support production ingestion and transformation pipelines using Databricks, Delta Lake, Unity Catalog, Apache Spark, Python/PySpark, and Databricks SQL. - Independently design and implement relational and dimensional data models for assigned data products, including fact tables, conformed dimensions, star schemas, and slowly changing dimensions (SCD Type 1/2).
- Experience building production ETL/ELT pipelines, implementing incremental processing, and supporting operational data quality and monitoring. - Strong SQL and Python/PySpark skills, with hands-on Git, testing, code review, and CI/CD practices. - Associate degree in Computer Science, Information Systems, or a related field; equivalent professional experience or relevant technical certifications may be considered.
- Create and automate data quality checks, reconciliation, pipeline monitoring, alerting, exception handling, and recovery procedures for production operations. - Tune Spark workloads, Databricks SQL queries, Delta table layouts, job configuration, and compute usage to improve performance, reliability, and cost efficiency. - Develop reusable, maintainable code with Git, peer reviews, unit/integration tests, CI/CD, and repeatable Databricks deployment practices.
- 7+ years of related professional experience in data engineering, data warehousing, analytics engineering, or comparable roles. - 3+ years of hands-on Databricks production experience with Delta Lake, Unity Catalog, Spark/PySpark, and Databricks SQL. - 3+ years of meaningful relational or dimensional data modeling experience, including personally designing and deploying fact/dimension or integrated business models.
Position Summary The Senior Data Engineer - Databricks & Data Modeling will develop, deploy, and maintain production data pipelines and reusable data models within Winsupply's Databricks lakehouse on Google Cloud. This hands-on role combines strong Databricks engineering skills with practical relational and dimensional modeling expertise to convert complex source data into trusted Silver- and Gold-layer data products. Working within the Data Architecture & Engineering team, this individual will implement approved architectural standards, collaborate with business stakeholders, Data Governance, and IT, and take ownership of reliable, efficient delivery from source ingestion through production support. Accountabilities/Responsibilities
- Tune Spark workloads, Databricks SQL queries, Delta table layouts, job configuration, and compute usage to improve performance, reliability, and cost efficiency. - Develop reusable, maintainable code with Git, peer reviews, unit/integration tests, CI/CD, and repeatable Databricks deployment practices. - Partner with business process owners and Data Governance to understand operational workflows, validate entity definitions and business rules, and use that context to inform sound data modeling, quality, lineage, and access decisions.
Competencies for Success - Has delivered and supported Databricks pipelines and data products in production from raw ingestion through trusted analytical outputs. - Demonstrates strong modeling judgment grounded in business process knowledge: understands core entities, grain, keys, relationships, SCD Type 1/2, fact/dimension design, and reporting impacts.
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline. - Databricks Certified Data Engineer Professional or comparable Databricks certification. - Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles.
- Databricks Certified Data Engineer Professional or comparable Databricks certification. - Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles. - Kimball dimensional modeling, enterprise data governance, semantic modeling for Looker, or advanced Spark performance optimization.
- Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles. - Kimball dimensional modeling, enterprise data governance, semantic modeling for Looker, or advanced Spark performance optimization. - Experience integrating IBM/mainframe, DB2, distribution/supply-chain, financial, or pricing data.

Your next step

Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.

Applying through SmartRecruiters

  • Uploading your resume fills in the application form for you, so check what it filled before you send.

Already applied? Track this application

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Description

Position Summary

The Senior Data Engineer - Databricks & Data Modeling will develop, deploy, and maintain production data pipelines and reusable data models within Winsupply's Databricks lakehouse on Google Cloud. This hands-on role combines strong Databricks engineering skills with practical relational and dimensional modeling expertise to convert complex source data into trusted Silver- and Gold-layer data products. Working within the Data Architecture & Engineering team, this individual will implement approved architectural standards, collaborate with business stakeholders, Data Governance, and IT, and take ownership of reliable, efficient delivery from source ingestion through production support.

 

Accountabilities/Responsibilities

  • Build, test, deploy, and support production ingestion and transformation pipelines using Databricks, Delta Lake, Unity Catalog, Apache Spark, Python/PySpark, and Databricks SQL.
  • Independently design and implement relational and dimensional data models for assigned data products, including fact tables, conformed dimensions, star schemas, and slowly changing dimensions (SCD Type 1/2).
  • Translate core business processes and relationships among Customer, Product, Vendor, Purchasing, Inventory, Sales, and Pricing entities into accurate Silver-layer structures and reusable Gold-layer data products, working with Data Architecture leadership on complex model decisions.
  • Ingest and integrate batch and streaming data from ERP, relational, legacy/mainframe, fixed-width or delimited files, APIs, and cloud storage; handle schema changes, incremental loads, and CDC as appropriate.
  • Implement business keys, table grain, joins, deduplication, history handling, and source-to-target mappings that produce repeatable, traceable results.
  • Create and automate data quality checks, reconciliation, pipeline monitoring, alerting, exception handling, and recovery procedures for production operations.
  • Tune Spark workloads, Databricks SQL queries, Delta table layouts, job configuration, and compute usage to improve performance, reliability, and cost efficiency.
  • Develop reusable, maintainable code with Git, peer reviews, unit/integration tests, CI/CD, and repeatable Databricks deployment practices.
  • Partner with business process owners and Data Governance to understand operational workflows, validate entity definitions and business rules, and use that context to inform sound data modeling, quality, lineage, and access decisions.
  • Document pipelines, models, transformation logic, dependencies, and runbooks so solutions can be maintained and supported by the broader team.
  • Troubleshoot data defects and pipeline failures, identify root causes, and drive fixes through production with appropriate communication and ownership.
  • Collaborate with the architecture team, DaaS, IT, and delivery partners; contribute practical recommendations and mentor peers while supporting approved technical direction.

 

Competencies for Success

  • Has delivered and supported Databricks pipelines and data products in production from raw ingestion through trusted analytical outputs.
  •  Demonstrates strong modeling judgment grounded in business process knowledge: understands core entities, grain, keys, relationships, SCD Type 1/2, fact/dimension design, and reporting impacts.
  •  Troubleshoots distributed data processing, data-quality discrepancies, and performance issues with a structured, evidence-based approach.
  •  Communicates clearly, challenges proposed solutions constructively, and collaborates across technical and business teams.
  •  Takes ownership of code quality, documentation, reliability, cost awareness, and delivery commitments. Qualifications/Experience

Qualifications

Minimum Qualifications

  • 7+ years of related professional experience in data engineering, data warehousing, analytics engineering, or comparable roles.
  •  3+ years of hands-on Databricks production experience with Delta Lake, Unity Catalog, Spark/PySpark, and Databricks SQL.
  •  3+ years of meaningful relational or dimensional data modeling experience, including personally designing and deploying fact/dimension or integrated business models.
  •  Foundational understanding of core business processes and entities (e.g., Customer, Product, Vendor, Purchasing, Inventory, Sales, and Pricing), with the ability to validate relationships with business stakeholders and apply that context to data modeling and governance decisions.
  •  Experience building production ETL/ELT pipelines, implementing incremental processing, and supporting operational data quality and monitoring.
  • Strong SQL and Python/PySpark skills, with hands-on Git, testing, code review, and CI/CD practices.
  •  Associate degree in Computer Science, Information Systems, or a related field; equivalent professional experience or relevant technical certifications may be considered.

 

Preferred Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
  • Databricks Certified Data Engineer Professional or comparable Databricks certification.
  • Experience with Databricks on Google Cloud, Lakeflow pipelines/jobs, Auto Loader, CDC, and Declarative Automation Bundles.
  • Kimball dimensional modeling, enterprise data governance, semantic modeling for Looker, or advanced Spark performance optimization.
  • Experience integrating IBM/mainframe, DB2, distribution/supply-chain, financial, or pricing data.

Additional Information

Physical Demands

The physical demands here are representative of those that must be met to successfully perform the essential job functions with or without reasonable accommodations:

  • Sitting for extended periods of time
  • Dexterity of hands and fingers to operate a computer keyboard, mouse, power tools, and other computer components
  • Lifting and transporting of moderately heavy objects, such as computers and peripherals
  • Occasional travel to interact with local companies, regional offices and/or support implementation of solutions

We are committed to inclusion, diversity, and equal employment opportunity, regardless of race, color, ancestry, religion, sex, gender, national origin, sexual orientation, age, citizenship, marital status, disability, veteran status, or any other factor protected by applicable federal, state, or local laws.

Company Description

Winsupply is in the business of creating and enabling entrepreneurs to achieve their dreams through wholesale distribution. Winsupply is a group of over 670 locally-owned companies that operate across a variety of industries, including HVAC, Plumbing, Electrical and more. The purpose of the support services campus is to eliminate obstacles and provide support to help our entrepreneurs succeed. Support service employees assist entrepreneurs in achieving their dreams through finance, accounting, IT, and other back-office operations.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Moraine, OH, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization
- Occasional travel to interact with local companies, regional offices and/or support implementation of solutions We are committed to inclusion, diversity, and equal employment opportunity, regardless of race, color, ancestry, religion, sex, gender, national origin, sexual orientation, age, citizenship, marital status, disability, veteran status, or any other factor protected by applicable federal, state, or local laws. Company Description

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.