Analytics Engineer
Victory Live is a private equity backed technology company aimed at maximizing distribution and yield for live event ticket inventory. We provide an end-to-end software platform for the live ticketing industry, managing thousands of sports, theater and live music event tickets on behalf of artists, promotors, teams, venues and professional resellers. Victory Live’s comprehensive offerings include an established B2B marketplace along with both a full-service and an automated SaaS platform to handle all elements of the ticket sales lifecycle, from ingestion to sales fulfillment. THE POSITION
The Analytics Engineer will support the business intelligence team by building reliable data pipelines, modeling data for reporting, and ensuring stakeholders have timely, accurate information. You’ll work closely with senior engineers and analysts, gaining hands-on experience with cloud data platforms, orchestration tools, and modern analytics workflows. RESPONSIBILITIES
- Develop, test, and maintain ETL/ELT pipelines using tools like dbt, Snowflake, Airflow, Dagster, and Azure Data Factory under the guidance of senior team members.
- Write efficient SQL and Python code to clean, transform, and load data from multiple sources.
- Assist with creating and maintaining data models (e.g. fact/dimension tables) for reporting and analysis.
- Support BI and reporting platforms (e.g. Sigma) by ensuring data is well-modeled and up to date.
- Help monitor pipelines and troubleshoot issues with data quality, performance, or reliability.
- Document data models, transformations, and workflows for knowledge sharing and reproducibility.
- Comfortable with APIs and integrating them into data pipelines.
- Collaborate with the BI team to translate business requirements into usable datasets and dashboards.
- Participate in code reviews, testing, and version control (Git) to ensure data integrity and consistency.
What we’re looking for
- 2–3 years of experience in data engineering, analytics engineering, or a similar role.
- Strong SQL skills and experience writing queries for analysis or transformation.
- Basic proficiency in Python for data processing and automation.
- Hands-on experience with a cloud data warehouse (Snowflake preferred).
- Familiarity with dbt or similar transformation frameworks.
- Exposure to workflow orchestration tools (Airflow, Dagster, etc.) or ETL/ELT services (ADF, Fivetran, etc.).
- Understanding of core data concepts: relational databases, schemas, joins, data modeling.
- Strong communication and problem-solving skills with an eagerness to learn new tools and techniques.
- Experience with business intelligence tools (Sigma, Power BI, Looker, or Tableau).
- Familiarity with Git and collaborative software development practices.
- Knowledge of basic data governance, lineage, and data quality practices.
- Exposure to cloud environments (Azure, AWS, or GCP).
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