PIIM Analytics Engineer

Bechtel Corporation•Houston, TX

47d•Onsite

About The Position

Bechtel is seeking an analytics engineer to design, build, and maintain scalable data pipelines and data integration solutions that support project execution. This role will manage data ingestion, transformation, and exchange across project systems and serve as a subject matter expert for the project’s analytics data lake environment. As part of a solutions-oriented team, the engineer will also support the implementation of applied AI/ML and low-code automation use cases, helping enable innovative, data-driven workflows across the project. The role will ensure reliable, high-quality data is available to support reporting, decision-making, and operational performance. The PIIM Analytics Engineer position reports to the PIIM Analytics Lead under the PIIM team. The PIIM team is responsible for aggregating and analyzing project data, developing automated reporting processes and client-required reports, maintaining high quality and insightful analytics, and assisting with the managing records across the project.

Requirements

Requires bachelor's degree (or international equivalent) and 5-8 years of relevant experience or 9-12 years of relevant work experience
Strong programming experience (Python, Scala, or equivalent) with a focus on data engineering and pipeline development.
Experience building and maintaining data pipelines and workflows (batch and/or streaming).
Strong SQL and data modeling experience in relational databases (e.g., MSSQL, PL/SQL).
Experience integrating data across systems using APIs, services, or data exchange frameworks.
Experience with cloud-based data platforms (e.g., Azure Databricks, data lakes, Delta Lake).
Understanding of data architecture, partitioning strategies, and performance optimization.
Experience supporting cross-functional teams in a project environment.
Experience delivering datasets for BI tools such as Power BI.
Experience with Azure Databricks and Delta Lake environments.
Familiarity with data governance, access control, and data quality frameworks.
Familiarity with applying AI/ML or low-code AI tools in production environments (e.g., integrating model outputs into data pipelines or workflows).

Responsibilities

Develop and maintain scalable data pipelines and workflows to ingest, transform, and provision data from multiple project systems into the analytics data lake.
Manage data ingestion and exchange across tools, ensuring reliable, timely, and accurate data movement between systems.
Serve as the on-site subject matter expert for the analytics data lake environment, including data architecture, access patterns, performance optimization, and support for advanced analytics use cases.
Collaborate with project teams and system owners to define data requirements, onboard new data sources, and ensure seamless system integration.
Build and maintain ETL/ELT processes, optimize SQL data models, and deliver curated datasets for reporting and downstream applications.
Ensure data quality, consistency, and completeness across sources to enable trusted project reporting and analytics.
Support reporting solutions by delivering performant, well-structured datasets for tools such as Power BI.
Support the development and deployment of low- to medium-complexity AI/ML and agent-based solutions by preparing data, integrating models into workflows, and operationalizing outputs within project systems.
Enable data-driven solutions including automation and applied AI/ML use cases that enhance project execution and efficiency.