Data Engineer-Kiewit Nuclear Solutions

Position Overview

The Technical Systems Analyst / Data Engineer supports enterprise-scale project data platforms that power analytics, reporting, and application integration across Kiewit’s business. This role operates within the Digital Project Execution (DPE) team and is responsible for designing, building, and optimizing modern data pipelines and cloud-based data architectures.

This position combines hands-on data engineering with cross-functional collaboration. The individual will work closely with Project Managers, Digital Execution Managers, Product Managers, Architects, Business Analysts, and core Technology teams to deliver reliable, scalable, and high-performance data solutions.

The ideal candidate is both technically strong / business-aware, and capable of translating complex project workflows into durable, well-architected data systems.

District Overview

This position is within the Kiewit Technology Group, supporting Kiewit Nuclear Solutions. 

Location

This is a remote position that may require some travel. 

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Responsibilities

Data Engineering & Architecture

• Design, build, and maintain scalable ETL/ELT pipelines using Azure Databricks (PySpark, Spark SQL) as the primary platform.
• Develop and optimize batch, streaming, and micro-batch processing architectures.
• Implement data ingestion workflows using Azure Data Factory, Azure Data Lake, SQL Server, and Snowflake.
• Design data models that support analytics, reporting, and database-driven application integration.
• Optimize performance of large-scale data systems, including query tuning and workload optimization.

Platform & Operations

• Support day-to-day operations of enterprise data platforms.
• Troubleshoot end-to-end data pipeline issues across ingestion, transformation, storage, and consumption layers.
• Implement data quality checks, validation rules, and monitoring processes.
• Contribute to architectural standards, governance frameworks, and documentation.

Collaboration & Business Enablement

• Partner with project teams to understand complex business rules and translate them into scalable data solutions.
• Support visualization and analytics teams by delivering clean, structured, high-performance datasets.
• Contribute to continuous improvement of data processes, standards, and best practices.
• Stay aligned with evolving Kiewit data strategies and emerging industry technologies.

Qualifications

Technology stack

Primary:

• Azure Databricks (PySpark, Spark SQL)
• Azure Data Lake
• Azure Data Factory
• SQL Server
• Snowflake

Supporting:

• Python
• Git (source control)
• Data modeling and warehousing frameworks

Required qualifications

• 6+ years of experience in Data Engineering, Data Analytics, Data Warehousing, or related roles.
• Experience in Azure-based architectures.
• Strong proficiency in advanced SQL development and performance optimization.
• Hands-on experience building ETL/ELT pipelines in a cloud environment.
• Familiarity with EPC / construction industry workflows highly preferred.
• Experience with Databricks or Spark-based distributed data processing.
• Experience troubleshooting complex data workflows across multiple systems.
• Strong understanding of data modeling principles (relational and dimensional).
• Experience documenting functional requirements, technical designs, and data workflows.
• Excellent written and verbal communication skills.

PREFERRED QUALIFICATIONS

• Familiarity with CI/CD and version control practices (Git).
• Experience implementing data quality frameworks and governance processes.
• Experience supporting enterprise-scale analytics environments.

BONUS EXPERIENCE

• Knowledge of engineering design tool ecosystems (Hexagon Smart Suite).
• Experience supporting data environments tied to project lifecycle systems.
• Exposure to large-scale project-based data environments.