Senior Data Engineer

Vantage Risk•Chicago, IL

2d•Hybrid

About The Position

At Vantage, the Data Engineer is mainly 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 an expertise in Data Modeling and Data Pipeline development within an Analytical, column-oriented data warehouse. This role reports to our Data Engineering Lead and is a remote opportunity/hybrid opportunity where the candidate is in a commutable distance to one of Vantage’s office locations, with a preferred location in New York or Chicago. The base salary expectation for this role is between $120,000 and $160,000. Additionally, Vantage offers its colleagues performance-based bonus potential, strong health & welfare benefits, retirement plans with company match, competitive time off plans, a highly flexible work environment, and much more.

Requirements

Bachelor’s degree in computer science or equivalent professional experience required.
Minimum of 5 years of experience in ELT development within a Data Warehouse.
Minimum of 5 years working with Dimensional Data Modeling, such as Kimball, Data Vault, or Medallion Architecture.
Strong familiarity with dbt and dagster/airflow.
Good working knowledge of distributed data and Kubernetes.
Expertise in data modeling using append-only replication methods to produce point-in-time data marts.
Strong understanding of test-driven development applied to Enterprise Data.
Strong familiarity with git and CI best practices.
Expertise in Python and SQL.
Expertise in column-oriented SQL modeling.

Nice To Haves

Experience in P&C Insurance or Financial Services Industry is a plus.
Ability to process and adapt to change in a rapid growth company environment.
Vantage associates are expected to be curious, thrifty, and resourceful to manage through the unknowns of growing a specialty (re)insurance business from the ground up.

Responsibilities

Translate requirements and data mapping documents into a technical design.
SQL development using dbt.
Pipeline development using dagster.
Talent for identifying the specific records that are produced from 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.