Senior IT Infrastructure Engineer, Data Engineering

About Acrisure

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:

As a member of our Infrastructure Engineering team, the Sr. IT Infrastructure Engineer, Data Engineering will be responsible for designing, developing, and maintaining our SQL database architecture. You will play a key role in understanding data warehouse technologies and ensuring efficient data storage and retrieval. The ideal candidate will have a strong background in SQL database management systems, data modeling, and data integration processes. Additionally, you should possess excellent problem-solving skills and the ability to collaborate effectively with cross-functional teams. 

Responsibilities: 

• Design, develop, and optimize SQL database architecture to ensure efficient data storage and retrieval. 
• Collaborate with cross-functional teams to gather and analyze business requirements for data engineering projects. 
• Assist in legacy application refactoring efforts, working closely with the development teams to modernize and optimize data processing and storage components.  
• Evaluate and recommend appropriate data warehouse solutions, including ETL processes, data pipelines, and data transformation workflows. 
• Possess a strong understanding of Databricks and other data lakehouse tooling, leveraging them to implement scalable and efficient data processing workflows. 
• Evaluate and recommend appropriate data warehouse technologies and tools based on project requirements and organizational needs. 
• Implement data engineering best practices, standards, and guidelines to ensure data integrity and quality. 
• Monitor and troubleshoot database performance issues, identifying and resolving bottlenecks and inefficiencies. 
• Collaborate with data analysts and data scientists to understand their data requirements and provide necessary infrastructure and support. 
• Stay up to date with emerging trends and advancements in data engineering and evaluate their potential impact on our systems and processes. 

Requirements: 

• Strong knowledge of SQL database architecture, data modeling, and data warehousing concepts. 
• Proficiency in designing and optimizing complex SQL queries, stored procedures, and database schemas. 
• Experience in refactoring legacy applications to improve data processing and storage efficiency. 
• Experience with data warehouse technologies such as Amazon Redshift, Google BigQuery, or Snowflake. 
• Familiarity with Databricks and other data lakehouse tooling, including Apache Spark and Delta Lake, to enable advanced data processing and analytics capabilities. 
• Familiarity with ETL tools and data integration processes. 
• Solid understanding of data governance and data management best practices. 
• Excellent problem-solving skills and ability to identify and resolve performance and scalability issues. 
• Strong collaboration and communication skills to effectively work with cross-functional teams. 
• Ability to work in a fast-paced environment and manage multiple projects simultaneously. 
• Detail-oriented with a commitment to delivering high-quality results. 
• Continuous learning mindset and a passion for keeping up with the latest advancements in data engineering. 

Education and Experience: 

• Proven experience in SQL database design, development, and optimization. 
• Previous experience as a senior data engineer or similar role. 
• Knowledge of programming languages such as Python or Java is a plus. 
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services is advantageous. 
• Certifications in relevant data engineering technologies or methodologies are desirable. 
• Candidates should be comfortable with an on-site presence to support collaboration, team leadership, and cross-functional partnership. 

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Candidates should be comfortable with an on-site presence to support collaboration, team leadership, and cross-functional partnership.