Senior Data Engineer

Responsibilities

The Senior Data Engineer will build and evolve reusable data pipelines and models to unify enterprise data across various cloud platforms. They are responsible for mentoring team members, ensuring high-quality engineering standards, and collaborating with stakeholders to translate business requirements into scalable technical solutions.

Requirements

Candidates must have 8-10+ years of experience in data engineering with strong proficiency in Python, Scala, or Java and SQL. A solid understanding of modern lakehouse architectures, cloud platforms like GCP or Azure, and engineering fundamentals such as CI/CD and automated testing is required.

Skills

• Data Engineering
• Python
• Scala
• SQL
• Databricks
• Apache Spark
• Delta Lake
• Apache Iceberg
• BigQuery
• Azure
• Data Modeling
• CI/CD
• Data Pipelines
• Cloud Platforms
• Software Engineering
• Mentoring

Benefits

• Medical Insurance
• Dental Insurance
• Vision Insurance
• Short-Term Disability Insurance
• Long-Term Disability Insurance
• Group Life Insurance
• Employee Assistance Program
• Calm App Subscription
• Pet Insurance
• 401(k) with company match
• Flexible Spending Account
• Health Savings Account
• Commuter benefits
• Paid maternity leave
• Paid paternity leave
• Fertility benefits

About this role

Senior Data Engineer

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 solutions to grow boldly forward. Bringing cutting-edge technology and top-tier human support together, it connects clients with personalized solutions across a range of insurance, reinsurance, payroll, benefits, cybersecurity, real estate services – and beyond. Since 2013, Acrisure has grown in revenue from $38 million to $5 billion and employs 20,000 colleagues in 19 countries. And this is just the beginning. To learn more, visit Acrisure.com.

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 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 that can power analytics, AI applications, operational workflows, and enterprise business processes.
Lead through technical expertise and collaboration, contributing to design discussions, guiding technical decisions, mentoring other engineers, and sharing patterns, learnings, and best practices across the team.
Proactively identify gaps and opportunities in the data platform, tooling, and engineering processes, and drive practical improvements that increase the team's overall execution and impact.

You may be fit for this role if you have:

8–10+ years of experience in software or data engineering, with experience building and supporting enterprise data platforms, data warehouses, lakehouses, or data-intensive applications.
Good hands-on data engineering experience, with strong SQL skills and proficiency in Python, Scala, or Java. You should be comfortable building complex data pipelines, transformations, reusable components, and data services.
Good understanding of modern lakehouse architecture, including Delta Lake, Apache Iceberg, data modeling, partitioning, schema evolution, incremental processing, CDC, data quality, and performance tuning.
Strong experience with Databricks, including Delta tables, Spark, batch and streaming pipelines, performance optimization, and scalable data engineering practices.
Experience working with cloud data platforms, especially GCP and/or Azure. Experience with technologies such as BigQuery, Azure, Databricks, Postgres, Dataflow, or similar platforms is valuable.
Experience with data orchestration and integration tools, such as Airflow, Dagster, Fivetran, dbt, APIs, CDC, and other batch or streaming technologies.
Palantir Foundry, Ontology, or AIP experience is a strong plus, but not mandatory. We are also looking for strong data engineers who have good engineering fundamentals and are willing to learn and work with Palantir technologies.
Quick learner who can pick up new platforms and technologies, understand how they work, and use them effectively to solve data engineering problems.
Good software engineering fundamentals, including modular design, version co...

About Acrisure Technology Group, LLC

Financial Services · 10,001+ employees · headquartered in Grand Rapids, Michigan · founded 2005