SENIOR DATA ENGINEER
On-siteErlanger, Kentucky, United States
Job Summary
Design and maintain scalable ETL/ELT pipelines using Microsoft Fabric and related cloud technologies while modernizing legacy SSIS and on-premises solutions to cloud-based Lakehouse architectures. Develop optimized data warehouse structures, implement automated ingestion processes with incremental loading, and establish governance to ensure analytics-ready datasets. Partner with Analytics and BI teams to deliver trusted data, mentor junior engineers on engineering standards, and troubleshoot production issues to improve operational reliability. This 100% onsite role in Erlanger, KY requires a Bachelor's degree and three years of enterprise pipeline experience.
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
- 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
- This position is 100% onsite, day 1 in our Erlanger, KY office
Desired 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
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