Data Engineer

KUBRA•Tempe, AZ

22h•Onsite

About The Position

We’re looking for a Data Engineer to join our Product Development - Business Intelligence team. In this role, you’ll build and maintain data pipelines and infrastructure that power BI products and client-facing reporting solutions. You’ll work closely with BI Analysts and product teams to ensure data is reliable, accessible, and structured to deliver meaningful insights to our clients.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, or a related field
3–5 years of experience in data engineering, preferably supporting BI or analytics teams
Hands-on experience with AWS or other cloud platforms
Strong experience building data pipelines (cloud or on-premise) using Python, SQL, Spark
Solid understanding of data modeling for analytics and reporting (e.g., star schemas, data warehousing concepts)
Strong proficiency in SQL and Python
Experience with tools/technologies such as Spark, Kafka, Databricks, Snowflake, Amazon Redshift, and dbt
Familiarity with BI tools and reporting environments such as Power BI or Tableau
Experience with streaming data using Kafka or similar technologies is an asset

Nice To Haves

Strong problem-solving mindset with a focus on data quality and reliability
Ability to translate business and BI requirements into scalable technical solutions
Collaborative approach with the ability to work across technical and non-technical teams
Proactive and self-driven, with a strong sense of ownership
Comfortable working in a fast-paced, product-focused environment
Strong attention to detail and commitment to continuous improvement

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines using Python, SQL, Spark, and dbt to support BI solutions
Develop and manage data infrastructure across SQL Server and AWS environments
Support migration of on-premise systems to AWS cloud platforms
Maintain and optimize SSIS packages and existing data workflows
Design and implement data models (e.g., star schemas) optimized for reporting and analytics
Partner with BI Analysts using tools such as Power BI/Tableau to deliver client reporting and data-driven insights
Automate manual data processes using Python and SQL to improve efficiency and data quality
Document data pipelines, models, and infrastructure across AWS, SQL Server, and Databricks environments
Collaborate with Product, BI, and Engineering teams to support BI product development leveraging Snowflake, Redshift, or Databricks
Stay current with emerging data and BI technologies including Kafka, Spark, dbt, and cloud-native tools
Participate in client-facing sessions when needed (design discussions, presentations, training), showcasing solutions built on AWS and modern data platforms