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Ibotta · 4 days ago

Analytics Engineer

Denver, CO

Full-time

Hybrid

Entry, Mid Level

$111K/yr - $127K/yr

2+ years exp

Ibotta is seeking an Analytics Engineer to join their innovative Core Data & Analytics team, contributing to their mission to Make Every Purchase Rewarding. The role involves organizing and optimizing data for analysis, collaborating with other engineers, and implementing best practices for data quality and integrity.

AppsCouponsE-CommerceMobileMobile AppsRetailService IndustryShopping

No H1B

Responsibilities

Helping us organize and optimize our data for analysis

Collaborate with other Analytics Engineers and Platform Engineers to understand our data models and translate them into scalable data solutions

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 (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

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

Qualification

Data pipelinesETL/ELT processesAWS EcoSystemPythonAirflowSQLSparkData visualizationCollaborationProblem-solvingCommunication skills

Required

2+ 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

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