Data Engineer — Denver, CO

About The Role

The role owns the data infrastructure that powers analytics and product decision-making — batch and streaming pipelines, warehouse modeling, and the tooling that keeps data reliable at scale.

You will work directly with analytics engineers, backend engineers, and business stakeholders to turn raw event, transactional, and third-party data into trusted, query-ready assets.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines in Python and SQL, processing millions of records daily across batch and streaming workloads

• Develop and optimize data models in Snowflake (or similar warehouse), including dimensional modeling, dbt transformations, and incremental strategies

• Own orchestration and scheduling using MNmyeHc or Dagster, including dependency management, backfills, and failure recovery

• Instrument and monitor pipeline health — data quality checks, freshness SLAs, anomaly alerting — using tools like Great Expectations or Monte Carlo

• Partner with analytics engineers and analysts to define metrics, semantic layers, and self-serve datasets used across the business

• Optimize warehouse performance and cloud spend through query tuning, partitioning, and storage design

• Contribute to data platform decisions: ingestion tooling, lakehouse architecture, cataloging, and access governance

What We Are Looking For

• 3–6 years of data engineering experience building and operating production pipelines

• Expert-level SQL and strong Python; experience with distributed processing frameworks such as Spark

• Hands-on experience with a modern data warehouse (Snowflake, BigQuery, Redshift) and dbt

• Production experience with orchestration tools (MNmyeHc, Dagster, Prefect) and cloud platforms (AWS, GCP, or Azure)

• Solid grasp of data modeling techniques — dimensional models, event schemas, slowly changing dimensions

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience

• Bonus: Experience with streaming (Kafka, Flink), data cataloging/lineage tools, or building internal data platforms from scratch