Senior Analytics Platform Engineer

Cars Commerce•Chicago, IL

10d•$104,100 - $130,150•Remote

About The Position

Join us in shaping a future of Automotive Commerce. Cars Commerce builds solutions for automotive dealerships, manufacturers, and consumers. Our driving force is to deliver a single platform that simplifies everything about buying and selling cars. Our Data and AI Platform team is embarking on a transformational journey, building innovative and integrated services that redefine how we deliver value to our customers and consumers alike. This is a rare opportunity to join a data-first company at a genuine inflection point — with strong leadership, a clear vision, and an enormous amount of meaningful work to be done. For a data professional who wants to build, create, and make a real impact — this is the place and the moment. As an Analytics Engineer on our Data Engineering Team, you will help revitalize our Data services and tooling across our platform with a comprehensive technical strategy to simplify and build scalable systems. This is an exceptional opportunity to shape the future of our platforms and drive meaningful change at scale, making a lasting impact within the automotive industry. Are you a data platform builder who loves owning things end-to-end? If so — we've got something really exciting for you! We're on a mission to build something truly foundational at Cars Commerce — a governed semantic/metrics layer, a data catalog, and a self-service analytics tool that puts the power of data directly into the hands of our business users. This isn't a maintenance role — this is a build-from-the-ground-up, make-your-mark opportunity! As our Analytics Engineer, you'll own the infrastructure, deployment, performance, and operations across all three platforms — deciding how each tool gets deployed, secured, monitored, and tuned for speed, reliability, and cost-efficiency in production. Real ownership. Real impact. You'll partner closely with our BI, Data Warehouse, Data Science, and ML Engineering teams — all depending on a healthy, well-performing data platform — while working right in the heart of our single source of truth initiative, built from the Data Lake up. This is a broad platform ownership role by design — semantic layer infrastructure, catalog administration, self-service BI tooling, and warehouse performance tuning all in one. A fast-moving, high-impact environment with a compelling AI roadmap, real-time data ambitions, and the unique challenge of unifying data across multiple platforms.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Five plus years of experience in data engineering or platform engineering, with meaningful ownership of production data infrastructure.
Deep, hands-on experience tuning Amazon Redshift for performance — distribution/sort key design and compression encoding, WLM or concurrency-scaling/Serverless configuration, materialized views and result caching for query acceleration, and reading/optimizing execution plans. This is a hard requirement.
Experience administering a data catalog or governance platform — Atlan, Collibra, Alation, DataHub, or similar.
Experience administering an enterprise BI or self-service analytics platform — Tableau Server/Cloud, Looker, Sigma, Omni, Power BI, or similar — including licensing, security model, and workspace/connection management.
Experience with a semantic layer, metrics layer, or query acceleration tool (Cube, Omni, dbt Semantic Layer, AtScale, LookML, or comparable), or a demonstrated ability to ramp quickly on a new one given the Redshift and platform-administration depth above.
Solid understanding of API layer design, authentication/authorization patterns, and row-level security implementation.
Experience with observability and monitoring tooling — Datadog, Metaplane, CloudWatch, or similar — including setting up alerting and being accountable for uptime.
Expertise in SQL or similar query languages (PL/SQL, DDL, HiveQL, or SparkSQL) for complex data manipulation.
Strong programming skills in Python, Scala, or Java, with a focus on automation and engineering efficiency.
Experience managing source code via GitHub and architecting CI/CD pipelines for data using Jenkins, GitHub Actions, or CircleCI.

Nice To Haves

Prior experience owning three or more of these tool categories (catalog, semantic layer, BI platform, warehouse performance) simultaneously on a lean team.
Experience supporting a BI platform migration (e.g., moving from one self-serve tool to another) from the infrastructure side.
Experience optimizing cloud data warehouse costs at scale (Redshift, Snowflake, or BigQuery).
Direct production experience with Cube.dev, Omni, or a comparable semantic layer product specifically

Responsibilities

Lead the technical architecture of our semantic and metrics layer, including infrastructure deployment, API design, pre-aggregation strategies, and enforcing robust authentication and row-level security protocols.
Manage the core governance infrastructure by administering Atlan—including crawl schedules and AI-driven enrichment—while maintaining the policy center for data access, PII classification, and compliance.
Oversee the self-service analytics platform operations, focusing on licensing, connection management, and version upgrades, ensuring high-quality platform administration rather than individual content creation.
Drive Amazon Redshift performance optimization in alignment with the platform, defining and tuning queries to support semantic layer pre-aggregation and business intelligence patterns.
Assume accountability for platform health, including uptime monitoring, observability alerting, and tracking compute and licensing expenditures across the data stack.
Provide technical leadership during tool migrations and contribute infrastructure and operability expertise to the evaluation and RFP processes for new semantic and BI technologies.