Data Engineer: Cloud Data Pipelines & EDW

Kforce Inc; Okemos (MI); On-site; USD 95,000 - 130,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

HSA

FSA

401(k)

Life insurance

Disability insurance

Paid time off

Job summary

Kforce is seeking a Data Engineer in Lansing, MI to support ETL, EDW, and data pipelines. The role emphasizes data integration, CDC, and moving data from on-premises environments to cloud platforms.

Candidates should have 3+ years in data engineering with Oracle/SQL Server/Snowflake experience and strong collaboration skills. Responsibilities include building ETL workflows, maintaining data warehouses, and contributing to improvements across the data engineering team.

Qualifications

• 3+ years of data engineering experience in ETL and data integration.
• Experience with Oracle, SQL Server, and Snowflake data platforms.
• Hands-on PL/SQL and T-SQL scripting and ETL tooling.
• Experience shipping EDW projects and data pipelines.
• Strong communication and teamwork across teams.

Responsibilities

• Develop and maintain ETL workflows and data pipelines.
• Move data from on-premises to cloud platforms using CDC techniques.
• Create and maintain data marts and EDW components.
• Automate data pipelines with stored procedures and scripting.
• Participate in on-call rotation and ensure change control.

Skills

Data engineering

ETL development

PL/SQL

T-SQL

CDC experience

Cloud data pipelines

SQL Server

Oracle

EDW concepts

Team collaboration

Tools

Snowflake

Oracle

SQL Server

Windows Server

RHEL

Job description

Kforce is seeking a Data Engineer in Lansing, MI to support ETL, EDW, and data pipelines. The role emphasizes data integration, CDC, and moving data from on-premises environments to cloud platforms.

Candidates should have 3+ years in data engineering with Oracle/SQL Server/Snowflake experience and strong collaboration skills. Responsibilities include building ETL workflows, maintaining data warehouses, and contributing to improvements across the data engineering team.