Senior Analytics Engineer, Core Data & Analytics

Ibotta is seeking a Senior Analytics Engineer, to join our innovative Core Data & Analytics team and contribute to our mission to Make Every Purchase Rewarding. You will be responsible for using the latest developments in ETL and ELT to provide the Revenue (Client Partnership and Client Sales) teams with trusted and curated datasets used as the foundation of critical data products that provide actionable insights. Additionally, you will take on a leadership role in cross-functional projects and within the team by mentoring junior team members in order to foster a collaborative work environment.

This position is located in Denver, Colorado, as a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Candidates must live in the United States.

What you will be doing:

• Be an Ibotta Data Ninja, helping us organize and optimize our data for analysis

• Serve as a mentor to junior Analytics Engineer team members 

• Collaborate with other Analytics Engineers and Client Analytics peers to define requirements and normalize datasets for use

• Identify, validate, document, and UAT event-based data for business use across the Revenue team

• Understand, and at times own, Revenue team business logic to help document, test, and maintain datasets

• Develop Revenue datasets with data quality principles in mind, creating standards and change management principles for events used in analytics workflows to ensure reliability

• Implement and utilize engineering best practices and methods to deploy and maintain quality, curated data sets using Airflow, including automated alerting and anomoly detection into data flows to ensure data quality and integrity

• Work across our full technology stack (Databricks, Spark, Command Line, Airflow, GitHub, Python, Monte Carlo, etc) to develop and maintain these datasets

• Building UI and automation tools to enable data democratization throughout the company

• Building automated altering and anomaly detection into data flow

• Lead large, complex task force projects that require cross-functional input across various teams

• Managing new data requirements and developing solutions that minimize technical debt creation

• Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere

What we are looking for:

• 5+ years of practical work experience in a data engineering role supporting an analytics team or equivalent experience as an analytics engineer

• Bachelor’s degree in Computer Science, Engineering, Analytics, or a related field required

• Working knowledge and some practical experience with some or all of the following:

  • End-to-end analytics automation, data pipelines, ETL/ELT processes, and tools (AWS Glue, DBT, etc.)

  • AWS EcoSystem and cloud-based data warehouse and architecture

  • Airflow, DataBricks, Git, Monte Carlo

  • Multiple languages and frameworks (Python, Scala, strong SQL, Spark, Command Line) highly preferred

  • Development in a modern BI/data visualization platform (Looker, Tableau, etc.)

  • Event-driven architectures and platforms are a strong plus

• An ability to develop solutions by applying data quality principles

• 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

• Exposure to managing and updating cluster configurations to ensure workflow operation

• Ownership of data throughout its lifecycle

• Excellent oral and written communication skills

Here are some of the traits that we seek in great analytics engineers:

You…

• are proactive, collaborative, and driven to solve hard problems while respecting diverse perspectives in a dynamic, fast-paced environment

• are an intellectually curious, conceptual thinker who uses creative problem-solving skills to work with other engineers and analytics stakeholders to challenge yourself and develop as an engineer

• are a detailed-oriented team player with an ownership mindset who develops technical solutions that apply data quality principles

• work collaboratively throughout the organization to drive towards common goals and understand the business context of data

• understand that delivering products incrementally helps provide more value to the business, and testing your code is one of the most important aspects of engineering

• trust your teammates, and embrace healthy conflict and debate - not afraid to voice your opinions but okay with not always being right