Data Engineer

Kubra•Tempe, AZ

12h

About The Position

KUBRA is seeking a Data Engineer to join our Product Development - Business Intelligence team. This role is responsible for building and maintaining data pipelines and infrastructure that support BI products and client-facing reporting solutions. The Data Engineer will collaborate closely with BI Analysts and product teams to ensure data is reliable, accessible, and structured to provide valuable insights to 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.
Candidates must ensure they have legal authorization to work in the U.S/ Canada.

Nice To Haves

Experience with streaming data using Kafka or similar technologies is an asset.

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.