Senior Data Engineer: Lakehouse & Cloud Pipelines (Onsite)

Fischer Homes; Erlanger (KY); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Health Insurance

Tuition Reimbursement

401(k) with Company matching

Employee Life Insurance

Personal time off

Job summary

The Fischer Group is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines on Microsoft Fabric, enabling analytics-ready data across the enterprise. You will modernize our data ecosystem by migrating legacy solutions and partnering with Analytics, BI, and IT teams to deliver trusted data.

Responsibilities include implementing data quality, governance, and monitoring, while mentoring other engineers and establishing standards for the growing Data Engineering team.

Qualifications

• Bachelor's degree in Computer Science, IT, or related field.
• 3+ years designing and supporting enterprise data pipelines (ETL/ELT).
• Strong SQL and Python (PySpark) proficiency.
• Experience with Microsoft Fabric, Azure Data Factory, Synapse, Databricks, Snowflake.
• Experience with source control and CI/CD.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines on Microsoft Fabric.
• Develop Lakehouse and Data Warehouse architectures for performance and cost efficiency.
• Migrate legacy SSIS and on-prem solutions to cloud platforms.
• Implement data quality, governance, and monitoring.
• Mentor junior engineers and establish engineering standards.

Skills

SQL

Python (PySpark)

Data modeling

Mentoring

Education

Bachelor's degree in Computer Science, Information Technology, or related field

Tools

Microsoft Fabric

Azure Data Factory

Azure Synapse

Databricks

Snowflake

Git

CI/CD

Job description

The Fischer Group is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines on Microsoft Fabric, enabling analytics-ready data across the enterprise. You will modernize our data ecosystem by migrating legacy solutions and partnering with Analytics, BI, and IT teams to deliver trusted data.

Responsibilities include implementing data quality, governance, and monitoring, while mentoring other engineers and establishing standards for the growing Data Engineering team.