The Tennessee Titans are looking for a Data Engineer to join our DevOps team. In this role you will own the pipelines and models that move data from source systems into our warehouse and make it usable for the business. Working in a modern data stack (Python, Airflow, dbt, Snowflake, AWS, and Docker) you will build and maintain ingestion into our layered warehouse, own the transformation models that turn raw source data into consumption-grade assets, and hold the line on the reliability and correctness of what analysts and applications depend on.
You will work closely with analysts, product stakeholders, and other engineers, and a significant part of the role is collaborating to deliver their needs through the data warehouse.
The Tennessee Titans are preparing to launch a new, innovative stadium in 2027, with new data sources across ticketing, concessions, access control, and fan engagement coming online as part of it. We are looking for individuals who thrive in a culture of collaboration, accountability, and continuous improvement, and who are driven to deliver meaningful results.
Primary Responsibilities- Build and operate batch and incremental ingestion from source systems into Snowflake, orchestrated in Airflow.
- Design and maintain dbt models across the ingestion, transformation, and consumption layers, with tests and documentation.
- Promote analyst-built logic into the appropriate layer so it becomes tested, supported, and reusable.
- Define consumer-facing data contracts (stable grain, stable naming) that analytics and applications can build on.
- Own data quality: define expectations, catch failures before consumers do, and keep pipeline issues diagnosable.
- Monitor pipeline runtime, freshness, and warehouse cost; troubleshoot failures and tune inefficient models.
- Write production-grade Python and SQL and build internal tools and APIs that serve data to business operations.
- Implement and improve CI/CD and deployment for containerized data workloads (Docker) across environments.
QualificationsRequired: - 1-3+ years of experience in data engineering, analytics engineering, or software development with substantial data work.
- Bachelor's or advanced degree in a relevant field such as Computer Science, Data Engineering, Information Systems, or equivalent practical experience.
- Proficiency in Python, including experience writing scripts, automating workflows, and building data pipelines.
- Strong SQL writing and tuning queries, transforming data, and working with structured datasets at scale.
- Experience with a cloud data warehouse (e.g., Snowflake, BigQuery, Redshift) and an understanding of how warehouse structure affects cost and performance.
- Understanding of data modeling grain, keys, and where transformation logic belongs.
- Exposure to CI/CD concepts, version control (Git), and software development best practices.
- Strong problem-solving skills and willingness to learn new technologies.
- Ability to work collaboratively in a team environment.
- Ability to handle sensitive information with discretion.
Preferred: - Experience with dbt in production, including tests, sources, and incremental models.
- Experience with a workflow orchestrator (e.g., Airflow).
- Experience with cloud platforms (AWS, Azure).
- Familiarity with Docker or containerized environments.
- Experience with data quality or observability tooling, or with building your own checks.
- Familiarity with API or web frameworks (e.g., Flask, FastAPI).
- Experience with Python-based data application frameworks (e.g., Streamlit, Dash, Panel) for building internal tools and dashboards.
- Knowledge of JavaScript or frontend frameworks (e.g., React, Vue) we are actively growing our frontend capabilities and value candidates interested in this area.
Core Competencies- Communication: Clearly conveys ideas in writing and verbally; adapts style to audience
- Collaboration: Works effectively across teams and functions; builds trust with stakeholders
- Problem Solving: Identifies root causes; develops practical, data-driven solutions
- Adaptability: Thrives in ambiguous or fast-changing environments
- Accountability: Takes ownership of results; follows through on commitments
- Customer Focus: Keeps end-user or client needs central to decisions and work product
Physical Requirements and Working Conditions- Work Environment: Office
- Physical Requirements: Ability to sit for extended periods of time; lift up to 25 lbs
- Schedule: Monday - Friday, standard business hours; occasional evenings
Those selected for further consideration will be contacted by someone from the Tennessee Titans.
