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Senior Data Engineer

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design, build, and maintain ETL/ELT pipelines on Microsoft Fabric

  • Migrate legacy SSIS and on-premises data solutions to cloud platforms

  • Develop and optimize Lakehouse and Data Warehouse architectures

  • Implement data quality testing, validation, and governance

  • Troubleshoot and resolve production pipeline issues

From the employer’s posting
Design, build, and maintain scalable ETL/ELT pipelines using Microsoft Fabric and related cloud technologies.
Modernize legacy SSIS and on-premises data solutions by migrating them to cloud-based platforms.
Develop and optimize Lakehouse and Data Warehouse architectures for performance, scalability, and cost efficiency.
Implement data quality testing, validation, and governance to ensure trusted, analytics-ready datasets.
Troubleshoot and resolve production pipeline issues while continuously improving reliability and operational performance.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
  • Strong proficiency in SQL and experience with Python
  • Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, Snowflake, or a similar cloud data platform.
  • Experience implementing data ingestion strategies, incremental loading, watermarking, and reliable pipeline architecture.
  • Experience with source control and CI/CD practices using Git or similar tools.

Preferred experience

  • PySpark preferred
  • Experience migrating legacy SSIS or on-premises data environments to cloud-based Lakehouse architectures.
  • 401(k) with Company matching contributions and profit-sharing
  • Experience with data quality frameworks, pipeline monitoring, and data contracts.
Qualification wording
Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
Strong proficiency in SQL and experience with Python (PySpark preferred).
Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, Snowflake, or a similar cloud data platform.
Experience implementing data ingestion strategies, incremental loading, watermarking, and reliable pipeline architecture.
Experience with source control and CI/CD practices using Git or similar tools.
Experience migrating legacy SSIS or on-premises data environments to cloud-based Lakehouse architectures.
401(k) with Company matching contributions and profit-sharing
Experience with data quality frameworks, pipeline monitoring, and data contracts.
Education & alternatives
Required Qualifications: - Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience. - Three (3)+ years of experience designing, building, and supporting enterprise data pipelines (ETL/ELT) in a production environment.
Apply at Fischer Homes

Posting record

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Open 3 monthsWe first saw this posting 102 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 25, 2026102 days ago
Recorded sightings
64
Last seen by us
Nov 4, 2026

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 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 102

Up longer than most. Similar jobs usually come down between day 6 and day 54.

From 11,032 similar postings that came down. Coming down is not always a hire.

Fischer Homes 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
  • Azure
  • Databricks
  • Snowflake
  • PySpark
Where the posting names them
- Three (3)+ years of experience designing, building, and supporting enterprise data pipelines (ETL/ELT) in a production environment. - Strong proficiency in SQL and experience with Python (PySpark preferred). - Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, Snowflake, or a similar cloud data platform.
- Strong proficiency in SQL and experience with Python (PySpark preferred). - Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, Snowflake, or a similar cloud data platform. - Experience implementing data ingestion strategies, incremental loading, watermarking, and reliable pipeline architecture.

Your next step

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,086.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 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 Summary

As a Senior Data Engineer, you will play a key role in building and evolving the data foundation that powers decision-making across The Fischer Group. You'll design, develop, and maintain scalable data pipelines and modern Lakehouse/Warehouse solutions on the Microsoft Fabric platform, ensuring business data is accurate, reliable, and analytics-ready. In this role, you'll help modernize our data ecosystem by migrating legacy solutions, establishing engineering best practices, and partnering with Analytics, Business Intelligence, and IT teams to deliver trusted data that drives business insights. If you enjoy solving complex data challenges, building cloud-native solutions, and shaping the future of enterprise analytics, this role offers the opportunity to make a lasting impact.

This position is 100% onsite, day 1 in our Erlanger, KY office.

You will thrive in this role if you:

  • Enjoy designing scalable data solutions that enable better business decisions.
  • Are passionate about building reliable, high-performing cloud data platforms.
  • Take ownership of data quality, governance, and pipeline reliability.
  • Enjoy solving complex technical challenges while continuously improving existing processes.
  • Thrive in collaborative environments where you partner with Analytics, Business Intelligence, and Software Development teams.
  • Stay current with emerging technologies and enjoy applying modern engineering practices to improve efficiency.
  • Like mentoring others and helping establish engineering standards across a growing team.

These skills will be used to:

  • Design, build, and maintain scalable ETL/ELT pipelines using Microsoft Fabric and related cloud technologies.
  • Develop and optimize Lakehouse and Data Warehouse architectures for performance, scalability, and cost efficiency.
  • Modernize legacy SSIS and on-premises data solutions by migrating them to cloud-based platforms.
  • Build reliable, automated data ingestion processes using incremental loading, orchestration, and monitoring best practices.
  • Implement data quality testing, validation, and governance to ensure trusted, analytics-ready datasets.
  • Partner with Analytics Engineering to deliver clean, curated data that supports enterprise reporting and self-service analytics.
  • Establish reusable engineering patterns, documentation, and development standards for the Data Engineering team.
  • Troubleshoot and resolve production pipeline issues while continuously improving reliability and operational performance.
  • Mentor junior engineers and contribute to continuous improvements in source control, CI/CD, and deployment processes.

Required Qualifications:

  • Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
  • Three (3)+ years of experience designing, building, and supporting enterprise data pipelines (ETL/ELT) in a production environment.
  • Strong proficiency in SQL and experience with Python (PySpark preferred).
  • Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, Snowflake, or a similar cloud data platform.
  • Experience implementing data ingestion strategies, incremental loading, watermarking, and reliable pipeline architecture.
  • Experience with source control and CI/CD practices using Git or similar tools.
  • Strong analytical, problem-solving, communication, and organizational skills.

Preferred Qualifications:

  • Microsoft Certified: Fabric Data Engineer Associate (DP-700), or actively pursuing certification.
  • Experience migrating legacy SSIS or on-premises data environments to cloud-based Lakehouse architectures.
  • Experience with data quality frameworks, pipeline monitoring, and data contracts.
  • Familiarity with dimensional modeling (Kimball methodology).
  • Experience working in Agile environments using Scrum or Kanban methodologies.
  • Experience mentoring or leading other Data Engineers.
  • Understanding of AI, Machine Learning, and generative AI technologies.
  • Experience implementing AI-enabled solutions or machine learning models within enterprise data environments.

Physical Demands and Work Environment:

  • Must be able to use verbal communication skills to effectively interact with associates, business partners, and customers.
  • Must be able to perform repetitive motions and use fine motor skills while operating standard office equipment.
  • Must be able to lift and carry approximately 20–25 pounds unassisted.
  • Must be able to remain seated for extended periods with occasional standing, walking, and reaching.

The Value of a Career with The Fischer Group
The Fischer Group is a family of companies focused on delivering exceptional experiences across homebuilding, financial services, and real estate. Through our businesses, we are committed to quality, growth, and long-term success for both our customers and our Associates.
We believe our success is driven by our people. We seek out talented individuals and provide the training, resources, and support needed to grow their careers and make a meaningful impact. The rewards for their efforts are:

  • Professional Development Training programs
  • Health Insurance
  • Tuition Reimbursement
  • Competitive Compensation
  • 401(k) with Company matching contributions and profit-sharing
  • Employee Life Insurance
  • Personal time off
  • Inclusive Leave

The Fischer Group holds the highest ethical standards of business. We are honest and straightforward and stand by our word. Our actions demonstrate respect, courtesy, and fairness.

 

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Location & working pattern

Erlanger, KY

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