Senior Analytics Engineer

Ibotta is seeking a Senior Analytics Engineer to join our Analytics organization and contribute to our mission to Make Every Purchase Rewarding.

In this role, you will provide embedded support to our revenue analytics team within Sales Operations, ensuring they have the data assets required to enable critical revenue and sales productivity reporting through improved source-of-truth data and optimized revenue data infrastructure. As Ibotta’s subject matter expert in revenue data, you will own the revenue data definitions and logic for a range of metrics and KPIs tracking the end-to-end sales process and work closely with other Ibotta data teams (Finance, Product) to ensure revenue analytics can access and use the right data at the right time to answer the right questions.

What you will be doing:

• Be an Ibotta Data Owner, 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 Analytics peers to define requirements and normalize datasets for use

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

• Understand, and often own, Sales Operations team business logic to help document, test, and maintain datasets

• Develop revenue-related 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 anomaly detection into data flows to ensure data quality and integrity

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

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

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

• Manage new data requirements and develop solutions that minimize technical debt

• Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency, & A great 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

• Direct experience working with sales teams and revenue-related data, including building connections to data sourced from Salesforce, strongly preferred

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

  • End-to-end data pipelines anrd 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) highly preferred

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

  • Event-driven architectures and platforms a strong plus

• An ability to develop solutions by applying data quality principles

• Ability to think creatively, provide thoughtful insights, and proactively 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 p