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Software Engineer, Data (L1) 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 accomplish 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 Software Engineer, Data (L1) is responsible for building technology and pipelines to rapidly onboard raw datasets into our data platform from a wide variety of data sources and associated technologies. Responsibility includes hands-on contributions in a team environment. Ensuring high quality and best practices are maintained through the development cycle is key to this position. 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, Kotlin, Java, and JavaScript and make use of many frameworks including Dataflow, Apache Airflow, Apache Spark, dbt, Delta Lake, Apache Iceberg, Cloud AI Platform, Spring, and React.   Responsibilities: Leverage established patterns and establish new patterns as required to rapidly onboard new data sets into the data platform Establish repeatable, automated data management processes for managing sensitive information Own deliverables while also collaborating with and supporting others in a team setting including conducting and participating in design and code reviews Collaborate with product on priorities and approach and with other engineering and AI teams who would consume raw data Requirements 2+ years of engineering experience with data warehouses, data lakes or software engineering with a data emphasis Strong SQL knowledge Proficient in Scala, Python, or Java Well versed in Data Lake & Delta Lake Concepts Understanding of data security best practices Well versed in Databricks/BigQuery/Palantir usage in building enterprise data platforms Familiarity with implementing end-to-end data pipeline and Ontology development using Palantir platform is a plus Familiarity with data orchestration technologies like Airflow, Dagster, or Fivetran Experience with cloud environments; (GCP, Azure) a definite plus Familiar with DevOps process Experience creating and sharing standards, best practices, documentation, and reference examples for data warehouse, integration/ETL systems Apply a disciplined approach to testing software and data Experience working with APIs Well versed in common data frameworks such as Spark & Polars Undergraduate degree in computer science or related dis