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Fischer Homes

SENIOR DATA ENGINEER

Erlanger, Kentucky, United States

Location
Erlanger, Kentucky, United States
Work
On-site
Employment
Not stated
Level
Senior
Function
Data & AI
Pay
Not stated
Posted
3 months ago

Pay and the market here

4 data jobs open in Erlanger: 0% remote, 1 posted in the last 30 days.

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About the role

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.

Source

Posted by Fischer Homes on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:28 UTC; the original is the reference.

View the original ad ↗

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