Data Analytics Engineer / Architect

Infopro Digital•Nashville, TN

6d•Onsite

About The Position

Infopro Digital is seeking a Data Analytics Engineer / Architect to join the Infopro Digital Automotive team in Nashville, TN. This role is on a permanent contract. Infopro Digital Automotive develops digital tools and software for decision-makers in the automotive aftermarket industry, serving various stakeholders like car manufacturers, aftermarket parts producers, distributors, and workshops. As a Data Analytics Engineer / Architect, you will be instrumental in building scalable data models and transformation pipelines to support reliable business insights and advanced analytics. You will contribute to diverse projects, fostering skill development and expertise growth.

Requirements

Hands-on expertise in Snowflake and its data modeling capabilities for defining business entities, KPIs, and building semantic layers for BI and advanced analytics use cases.
Advanced SQL expertise with a strong focus on transformations and query performance.
Hands-on experience in dbt (models, tests, macros, and project structure).
Deep understanding of data modeling concepts such as dimensional modeling as well as Data Vault 2.0 and Anchor Modeling (or a strong willingness to learn both).
Ability to collaborate effectively with business stakeholders and translate requirements into scalable data models.
Maintain high standards for data quality, harmonization, and single-source-of-truth principles within Git-based development workflows.
Fluent English communication with international colleagues and stakeholders in the US and Europe.

Nice To Haves

Additional experience in Databricks.
Knowledge in Power BI (from a consumption perspective).
Experience with data testing frameworks (e.g., Great Expectations, DQX, Soda).
Familiarity with data cataloging and lineage tracking.
Understanding of feature engineering concepts for future ML use cases.

Responsibilities

Design, build, and optimize scalable data transformation pipelines with a strong focus on SQL performance and efficiency.
Maintain robust dbt projects including models, tests, macros, and structured project setups.
Develop and evolve data models using dimensional modeling principles (e.g., star schemas), Data Vault 2.0, and Anchor Modeling approaches in a combined modeling environment.
Define, standardize, and maintain business entities, KPIs, and metric logic as reusable assets.
Provide semantic layers consumable by BI tools and machine learning use cases.
Work closely with business stakeholders to translate requirements into scalable data models, ensuring alignment, data consistency, and a single-source-of-truth approach.
Leverage modern data platforms such as Snowflake and/or Databricks.
Contribute to collaborative, Git-based development workflows including code reviews and best practices.