Senior Software Engineer, Data (L3)
Austin, TX (Onsite 4 days per week)
Note: This is a full-time role and we do not offer C2C or C2H employment and are not able to sponsor visas for this position.
About Acrisure
Acrisure Enterprise Technology Group is where human expertise meets advanced technology.
A global fintech leader, Acrisure empowers millions of ambitious businesses and individuals with the right solutions to grow boldly forward. Bringing cutting-edge technology and top-tier human support together, we connect clients with customized solutions across a range of insurance, reinsurance, payroll, benefits, cybersecurity, mortgage services – and more.
In the last twelve years, Acrisure has grown in revenue from $38 million to almost $5 billion and employs over 19,000 colleagues in more than 20 countries. Acrisure was built on entrepreneurial spirit. Prioritizing leadership, accountability, and collaboration, we equip our teams to work at the highest levels possible.
Job Summary:
The Enterprise Data team’s mission is to unify data across the enterprise to optimize business decisions made at the strategic, tactical, and operational levels of the organization. We accom-plish this by building a data foundation utilizing Palantir Foundry, AIP and Ontology that powers analytics and reporting platforms, and business processes that provide quality data, in a timely fashion, from any channel of the company and present them in such a manner as to maximize the value of that data for both internal and external customers.
The Senior Software Engineer, Data Engineer is responsible for building technology and pipe-lines to rapidly model different and varying data sources into reusable data models that can be consumed by a wide variety of customers including operational applications as well as analytics & metrics. Responsibilities include hands-on contributions in a team environment, critical think-ing and developing technical solutions with business stakeholders and changing requirements, and mentoring engineers to ensure high-quality development and best practices are maintained throughout the delivery cycles.
Our Data platform is transitioning to Palantir from a Google and Microsoft hybrid cloud tech stack. Our data storage layer includes BigQuery, Databricks, Azure, and Postgres. Across our broader tech stack, we code primarily in Python, Scala, and JavaScript and make use of many frameworks including Dataflow, Apache Airflow, Apache Spark, dbt, Delta Lake, Apache Iceberg.
Here are some of the ways in which you’ll achieve impact:
Build and evolve reusable data engineering patterns that enable the rapid, scalable, and consistent onboarding of new data sources into the enterprise lakehouse.
Design and implement reliable, automated data management processes that improve data quality, security, governance, and the responsible handling of sensitive information.
Own major technical deliverables end to end , from solution design and development through testing, deployment, monitoring, and production support, while ensuring solutions meet business requirements and engineering standards.
Design and build reusable data models, pipelines, frameworks, and components that can support multiple business use cases and improve development velocity across the team.
Identify opportunities to improve performance, reliability, scalability, and maintainability , including addressing technical debt and establishing better engineering patterns and standards.
Apply disciplined engineering practices , including automated testing, data validation, CI/CD, observability, code reviews, and documentation, to deliver high-quality and production-ready data solutions.
Collaborate closely with Product and business stakeholders to understand priorities, translate business requirements and KPIs into technical solutions, and adapt effectively as requirements evolve.
Partner with Data, AI, and other engineering teams to provide trusted, well-modeled, and accessible data…