Analytics Engineer, Product Analytics

Ibotta•Denver, CO

1d•$113,000 - $132,000•Hybrid

About The Position

Ibotta is seeking an Analytics Engineer to join our Product Analytics team and contribute to our mission to Make Every Purchase Rewarding. This includes building scalable data pipelines and the data foundations that power product decisions across consumer products, client surfaces, and semantic layers, enabling the business to drive decisions using data. As an Analytics Engineer, you will use the latest developments in data ETL, support strategy development, build practical automation and tooling, and help maintain the data foundations Product Analytics relies on. Data is considered a strategic asset here at Ibotta. In this role, you’ll have a direct impact by making data available and reliable for Decision Scientists and Data Scientists to provide advanced analytics, models, and analyses to their business stakeholders.

Requirements

3+ years of practical work experience in a data engineering role supporting an analytics team, or equivalent experience as an analytics engineer or BI developer
Bachelor’s degree in Computer Science, Engineering, Analytics, Statistics, Economics, or a related field required
An ability to develop solutions by applying data quality principles, including schema validation and data contracts
Proven experience with Python and SQL, including building and maintaining production data pipelines (Databricks or similar cloud data warehouse experience a plus)
Ability to think creatively, provide thoughtful insights, and solve problems to answer business questions using data
Collaboration with SMEs to understand the business context of the data
Experience identifying and troubleshooting data anomalies and pipeline issues, including supporting CI/CD (GitHub Actions) and automated testing
Ownership of data throughout its lifecycle, including rollup and aggregation tables built from tracking and business events
Track record of successfully managing and updating cluster configurations to ensure workflow operation; familiarity with Airflow and growing platforms like Databricks Asset Bundles (DABs) a plus
Extensive experience with ETLing data; familiarity with Looker/LookML and development tooling supported by AI (e.g., Claude, Copilot) a plus

Nice To Haves

Databricks or similar cloud data warehouse experience a plus
Familiarity with Airflow and growing platforms like Databricks Asset Bundles (DABs) a plus
Familiarity with Looker/LookML and development tooling supported by AI (e.g., Claude, Copilot) a plus

Responsibilities

Collaborating cross-functionally with Decision Scientists to aggregate and normalize datasets for analysis
Partnering and collaborating with other data related teams, including engineering, data engineering, analytics engineering, and decision science, to represent data needs and best practices through the data development, validation, and managed process
Proactively incorporating the knowledge of how Decision Science solutions meet end customer needs into data preparation design and decisions
Identifying, validating, documenting, and testing events-based data for business utility in the data lake to help answer strategic questions
Understanding business logic to help document, test, and maintain datasets
Developing data sets with data quality principles in mind; creating standards and change management principles for events used in analytics workflows to ensure reliability
Deploying and maintaining data pipelines using Airflow (with growing exposure to Databricks Asset Bundles/DABs as the team migrates), and supporting CI/CD and automated testing (GitHub Actions) to keep pipelines reliable
Building UI and automation tools to enable data democratization throughout the company
Building automated alerting and anomaly detection (e.g., Monte Carlo or similar tooling) into data flows to catch issues early
Owning multiple projects end to end, partnering with the Sr. Analytics Engineer on larger initiatives, and developing solutions that minimize technical debt creation
Exploring tooling supported by AI (e.g., Claude skills and plugins) to improve day to day engineering workflows
Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency & A good idea can come from anywhere