Senior Analytics Platform Engineer

Cars.com•Chicago, IL

9d•Remote

About The Position

Join the Data and AI Platform team at Cars Commerce as they embark on a transformational journey to build innovative and integrated services that redefine how value is delivered to customers and consumers. 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. This role is for a data professional who wants to build, create, and make a real impact. As an Analytics Engineer on the Data Engineering Team, you will help revitalize data services and tooling across the 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. The role involves building foundational elements like a governed semantic/metrics layer, a data catalog, and a self-service analytics tool. This is a build-from-the-ground-up opportunity where you will own the infrastructure, deployment, performance, and operations across these platforms, deciding how each tool is deployed, secured, monitored, and tuned for speed, reliability, and cost-efficiency in production. You will partner closely with BI, Data Warehouse, Data Science, and ML Engineering teams, working within the single source of truth initiative. This is a broad platform ownership role encompassing semantic layer infrastructure, catalog administration, self-service BI tooling, and warehouse performance tuning. The environment is fast-moving with a compelling AI roadmap, real-time data ambitions, and the 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.
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.