Data Engineer II

FHLBank•Topeka, KS

3d•Hybrid

About The Position

We are seeking a Data Engineer to design, build, and maintain scalable data solutions that support enterprise reporting, analytics, and data modernization initiatives. In this role, you will develop and operationalize batch and streaming data pipelines, optimize data workflows, and collaborate across teams to deliver high-quality, maintainable solutions.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Mathematics, Business, or related field; or equivalent combination of education and experience.
4–6 years of data engineering or related professional experience.
Strong experience with SQL Server, Azure, Databricks, ETL/ELT processes, job scheduling, and data streaming services.
Experience building scalable, production-ready end-to-end data solutions in cloud or big data platforms.
Strong programming and scripting skills, including Python.
Experience with REST APIs for data ingestion.
Experience supporting production operations in a DevOps environment.
Knowledge of data warehousing concepts and data modeling standards.
Strong analytical, problem-solving, and root cause analysis skills.
Ability to communicate technical concepts clearly to both technical and non-technical audiences.

Nice To Haves

Experience with C#, VB, or similar object-oriented programming languages for maintaining legacy ETL applications.
Experience with data visualization and reporting tools such as Power BI or IBM Cognos.
Passion for data analysis and storytelling with data.
Experience working with IT leadership to establish and improve data management processes and procedures.
Demonstrated ability to mentor junior team members and work effectively in a collaborative, team-oriented environment.

Responsibilities

Design, develop, test, and deploy batch and streaming data ingestion pipelines across multiple data domains.
Build and automate ETL/ELT processes using scripting languages, ETL tools, and job scheduling software.
Use Azure technologies and Databricks to develop scalable, reliable, and high-performing data pipelines.
Partner with business analysts, data analysts, technical SMEs, and cross-functional teams to gather requirements and deliver data solutions.
Ensure pipelines are fault-tolerant, low-latency, and maintainable through strong engineering and automation practices.
Support data modernization efforts by optimizing legacy processes and implementing cloud-based solutions.
Provide production support, system monitoring, troubleshooting, and root cause analysis.
Collaborate with audit and governance partners to document data lineage and support data audits.
Guide junior team members, contribute technical leadership, and communicate effectively with technical and non-technical stakeholders.