Position Overview

The Data Engineer is responsible for designing, developing, and maintaining scalable, reliable, and secure data pipelines within a modern data platform environment. This role supports self-service data consumption, reporting, analytics, and ensures data quality, integrity, and compliance. This role offers opportunity for professional development, certifications, and career advancement, exposure to large-scale, structured and unstructured data environments and participation in a dynamic, innovative, and supportive team culture.

District Overview

Kiewit Technology Group builds solutions to enable and support our company's expansive operations. Our mission is to deliver project schedule and cost certainty by employing technology designed by and for the construction industry. Our team utilizes systems and tools that manage every part of Kiewit's business and the project lifecycle to improve planning and day-to-day execution in the field. We give our people real-time data to make faster, smarter decisions. 

Location

This is an in-office role located on our LaVista, NE campus. This is not a remote opportunity and requires regular, daily attendance.

Responsibilities

• Design, develop, and optimize data pipelines and ETL/ELT processes for ingesting, transforming, and loading data from diverse sources (databases, file systems, cloud platforms) into BI and analytics platforms (e.g., Snowflake, Azure Data Lake, SQL Server).
• Implement data orchestration using modern tools (e.g., Airflow, Prefect, Azure Data Factory).
• Collaborate with data scientists, analysts, business stakeholders, and cross-functional IT teams to understand data requirements and deliver solutions.
• Contribute to data modeling (star/snowflake schema), documentation, and metadata management.
• Ensure data quality, integrity, and compliance with relevant standards and regulations (e.g., GDPR, HIPAA).
• Monitor, troubleshoot, and resolve production issues in a timely manner.
• Participate in agile delivery teams, including design and code review sessions, to ensure optimal, bug-free code is deployed to production.
• Support CI/CD processes and version control (e.g., Git) for data engineering workflows.
• Mentor junior engineers and contribute to team knowledge sharing and best practices.
• Stay current with emerging technologies and trends in data engineering, cloud platforms, and data governance.

Qualifications

• 2–5 years of experience in a data engineering role, preferably in a data warehouse or cloud data platform environment.
• Proficiency in SQL, data modeling, and performance optimization.
• Experience with ETL/ELT tools (e.g., Informatica, Azure Data Factory, dbt) and scripting languages (e.g., Python).
• Experience with data pipeline orchestration tools (e.g., Airflow, Prefect) and cloud platforms (AWS, Azure, GCP).
• Familiarity with containerization (Docker, Kubernetes) and infrastructure automation (Terraform) is a plus.
• Proven ability to interpret complex business rules and processes, and translate them into robust data integration solutions.
• Strong commitment to meeting deadlines and delivering high-quality solutions.
• Excellent interpersonal and communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• Demonstrated ability to work collaboratively in agile, cross-functional teams.
• Passion for continuous learning and professional development in the data engineering space. #LI-AK1