Principal Data Platform Architect

Position Overview

We are seeking a Principal Data Platform Architect to own the end-to-end technical vision for Kiewit's enterprise data platform. This is a senior individual contributor role spanning cloud infrastructure, data warehousing and analytics, ML/AI and citizen development enablement. This is an opportunity to shape all layers of a modern data stack enabling smarter decisions across estimating, scheduling, procurement, project controls, safety, and equipment management. You will be responsible for setting architecture standards, guiding technology decisions, and partnering with data engineering, data science, citizen developers, data governance and business leadership across estimating, operations, finance, procurement, and other critical business domains.

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 a full time in office role located on our LaVista, NE campus. We are not offering relocation for this role. 

Responsibilities

• Platform Architecture: Define and own the enterprise data platform architecture across cloud infrastructure, ingestion, storage, transformation, warehousing, and ML/AI/CitDev enablement layers.

• Cloud Infrastructure: Design scalable cloud-native infrastructure on Azure, AWS, or GCP, including managed compute, networking, storage, and orchestration to support diverse data workloads from batch ETL to real-time streaming.

• Data Warehousing & Analytics: Architect the enterprise data warehouse and lakehouse strategy, establishing standards for data modeling, semantic layers, and analytics delivery across business domains.

• ML/AI Platform Enablement: Build the technical foundation for ML/AI workloads: feature stores, ML pipelines, model serving infrastructure, and data contracts that bridge data engineering and data science.

• Agentic AI Frameworks: Define standards for how AI agents interact with Kiewit's data assets, establishing guardrails around data access, auditability, and output validation in agentic workflows.

• Citizen Development: Define guardrails, templates, and platform standards that empower citizen developers while maintaining data quality, security, and consistency across the enterprise.

• Governance & Quality: Establish platform governance including data quality frameworks, lineage tracking, metadata management, access controls, and compliance with enterprise security standards.

• Technology Strategy: Evaluate and guide adoption of modern data platform technologies (e.g., Databricks, Snowflake, dbt, Apache Iceberg, Kafka, Dagster,etc.) aligned to construction-industry needs.

• Technical Leadership: Provide architectural mentorship to senior and mid-level data engineers; influence cross-functional teams and shape engineering culture across the data organization.

• Stakeholder Partnership: Partner with project technology leads and business stakeholders to translate operational challenges into platform capabilities and communicate architectural decisions clearly to executive audiences.

Qualifications

• 10+ years in data engineering, data architecture, or data platform roles with increasing scope and seniority

• Demonstrated experience designing and owning large-scale data platforms spanning infrastructure, warehousing, and analytics

• Deep expertise in at least one major cloud provider (Azure, AWS, or GCP) including data-specific services

• Hands-on proficiency with modern lakehouse and warehouse technologies (e.g., Snowflake, Databricks, Delta Lake, Apache Iceberg)

• Strong proficiency in Python and/or Scala; experience with Spark or distributed compute frameworks

• Experience with data pipeline orchestration tools such as Airflow, Dagster, or Prefect

• Track record of leading architecture decisions and influencing engineering direction across multiple teams

• Excellent written and verbal communication skills; able to translate complex technical concepts for non-technical stakeholders

Preferred

• Familiarity with real-time data ingestion and streaming patterns (Simplement Roundhouse, SNP Glue, Kafka, or Azure Event Hubs)

• Background in data mesh or data product thinking; experience enabling self-service or citizens development data infrastructure

• Exposure to construction, engineering, or capital-project data environments, ERP systems, project controls, field operations data

• Relevant cloud or data certifications (AWS Solutions Architect, Azure Data Engineer, GCP Professional Data Engineer, dbt Analytics Engineer)