AVP, Data Engineer

Vantage Group Holdings•New York, NY

2d•Hybrid

About The Position

Vantage Group Holdings Ltd. is a specialty re/insurance company established in late 2020, with approximately 365 colleagues in the United States and Bermuda. The AVP, Data Engineer is primarily responsible for ingesting and transforming replicated source data into data products that are easily consumed by the Reporting team and other downstream users. The role requires expertise in data modeling and data pipeline development within an analytical, column-oriented data warehouse. It reports to the VP, Data Engineering & ETL Lead and is a hybrid opportunity for a candidate within commuting distance of a Vantage office, with New York or Chicago preferred. The base salary expectation is $175,000 to $210,000. The role also offers performance-based bonus potential, health and welfare benefits, retirement plans with company match, competitive time-off plans, and a flexible work environment. Vantage expects associates to be curious, thrifty, and resourceful while adapting to the uncertainties of growing a specialty (re)insurance business.

Requirements

Bachelor's degree in Computer Science or an equivalent combination of education and professional experience.
At least 8 years of Data Engineering experience designing, building, and supporting enterprise data platforms, ingestion frameworks, and transformation pipelines.
Strong expertise in SQL, Python, and dbt, including developing and optimizing large-scale ETL/ELT solutions.
Hands-on experience with Dagster, Airflow, or similar workflow orchestration tools.
Experience building and managing data ingestion and replication pipelines from relational databases such as PostgreSQL and Oracle, NoSQL sources, and file-based data feeds into Snowflake, Databricks, or comparable modern data platforms.
Deep understanding of data modeling, including dimensional modeling, Medallion Architecture, Data Vault, and highly relational data structures.
Experience transforming complex business data into trusted, consumable datasets for reporting, analytics, and downstream business users.
Strong knowledge of data engineering best practices, including testing, code reviews, Git version control, and CI/CD processes.
Familiarity with distributed data processing technologies, Kubernetes, and modern cloud-based data ecosystems.
Demonstrated ability to mentor junior engineers, conduct code reviews, and drive technical best practices across a team.
Proven ability to operate in a player-coach capacity, balancing hands-on development with technical leadership and team guidance.
Ability to process and adapt to change in a rapid-growth company environment.

Nice To Haves

Experience in the Property & Casualty Insurtech or Financial Services industry is preferred.

Responsibilities

Translate requirements and data mapping documents into a technical design.
Develop SQL using dbt.
Develop pipelines using Dagster.
Identify the specific records produced as a result of SQL bugs.
Debug and troubleshoot issues found during testing or production.
Communicate project status, issues, and blockers with the team.
Contribute to continuous improvement by identifying and addressing opportunities.
Mentor junior engineers, conduct code reviews, and advance technical best practices across a team.
Balance hands-on development with technical leadership and team guidance.