Top Senior Data Engineer Jobs in Denver & Boulder, CO

The Senior Data Engineer will design and manage data pipelines, work with complex datasets, and collaborate with teams to enhance data product integrity and effectiveness.

Design, build, and operate large-scale AWS-based ETL pipelines using Glue/PySpark to ingest, transform, and curate multi-format data into Apache Iceberg tables. Ensure data quality, metadata management, semantic layer creation (Trino/Athena), CloudFormation deployments, documentation, and compliance within a FedRAMP federal agile environment.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

As a Senior Data Engineer, you will architect and maintain data pipelines and ETL processes for analytics, collaborating with multidisciplinary teams to deliver impactful data solutions.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

The Data Architect & Strategy Lead will assess and optimize data operations, manage MongoDB performance, and implement modern data architecture and strategies, ensuring system reliability and performance.

The Sr. Data Engineer will build and maintain data pipelines, develop ETL processes, and optimize data infrastructure, collaborating across teams to ensure data reliability and performance.

Design, build, and maintain scalable ETL/data pipelines across distributed systems. Ensure data quality, integrity, security, and high availability. Monitor and optimize pipeline performance, perform root cause analysis, document systems, collaborate with global teams, and participate in on-call rotations to support production data systems.

Lead design and delivery of a cloud-based data platform: implement CDC/streaming ingestion, modeling, transformations, cross-region DB replication, observability, governance (PII, lineage, access), and enable downstream marts while mentoring engineers and driving IaC/automation-first practices.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Design, build, deploy, and operate scalable production data pipelines and workflows (Airflow, BigQuery, dbt). Own medium-sized platform initiatives end-to-end, ensure SLA-driven freshness, quality, and cost controls, implement monitoring and CI/CD, participate in on-call incident response, optimize warehouse performance, and collaborate with analytics, data science, product, and engineering stakeholders.

The Senior Data Engineer designs and maintains scalable data processing solutions, contributes to data ingestion, and collaborates across teams to optimize data workflows and pipelines.

Design, build, and maintain reliable data pipelines and models using SQL, Python, and Databricks/Spark. Translate multi-source schemas into scalable data models, enforce data hygiene and privacy, add tests/documentation/lineage, and collaborate with analytics, product, marketing, and vendor teams to deliver trustworthy data for personalization and marketing.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Design, build, and maintain data models, pipelines, and access layers to support care delivery, operations, and analytics. Ensure data quality, governance, and reliability while optimizing infrastructure and performance. Serve as a technical leader, review code, set engineering best practices, and collaborate cross-functionally to translate business needs into scalable data solutions.

Build and maintain scalable ETL pipelines using Python, Spark, and Airflow; collaborate with AI/ML and Product teams to deliver AI-native data products; identify and resolve ETL bottlenecks; ensure code quality through reviews and tests; own sprint deliverables and contribute to roadmap planning and major epics.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

The Senior Data Engineer will design and optimize data infrastructures and pipelines, lead projects, mentor juniors, and enforce best practices.

The Senior Data Engineer will design and implement ETL processes, develop data models, and ensure data quality, while mentoring junior engineers and managing multiple projects effectively.

Design and implement Lakehouse solutions and data pipelines, optimize Databricks environments, and integrate AI applications while delivering exceptional results for clients.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

The Senior Data Engineer designs and manages data warehouse infrastructure, develops ELT pipelines, ensures data security, and promotes data quality while collaborating with diverse stakeholders.

Design and optimize SQL Server solutions, manage data, automate processes with PowerShell, and integrate with external systems to enhance functionality.