Top Data Engineer Jobs in Provo, UT

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.

Design, build, and operate scalable batch and streaming data pipelines and a lakehouse on AWS. Implement ETL/ELT, CDC, metadata/catalog and governance, automated AWS provisioning (IaC), CI/CD for data pipelines, data quality and lineage, observability, and documentation while collaborating across teams.

Own day-to-day Snowflake administration and the Sigma semantic layer; manage ingestion (Fivetran), dbt modeling scope, reverse-ETL to Salesforce/HubSpot/NetSuite, data quality SLAs, reporting and dashboards, partner with managed data vendors, design automation and reproducible month-end financial analytics, and drive analysis and experiments for AdOps, Sales, and Finance.

Own and operate the Snowflake warehouse and Sigma semantic layer; manage ingestion (Fivetran), dbt model scoping and review, reverse-ETL, data quality SLAs, dashboards, month-end financial analytics, vendor management, and automation to support AdOps, Sales, Finance, and executive reporting.

The Sr. Data Engineer designs ETL solutions and data architecture, collaborates on technical solutions, and addresses data management functions.

Design, build, and maintain scalable ETL/ELT data pipelines and data platform architecture. Build programmatic pipelines (primarily Python), optimize analytical data models (SQL), integrate sources into Snowflake, use orchestration/transformation tools (dbt, Airflow, Dagster), improve data quality/observability, and partner with product, engineering, and analytics to deliver reliable data for decision-making.

Own and scale Provable's data platform on GCP: build and optimize ingestion pipelines from blockchain indexers, design privacy-aware data models, manage Postgres and BigQuery, develop high-performance data-serving APIs, ensure data quality and observability, and use IaC (Terraform, Helm) and Kubernetes to deploy and cost-optimize environments.