WHAT YOU HAVE:

Education, Experience, and Licensing:

• Bachelor’s degree in computer science, Information Technology, Engineering, or related field.
• Minimum 6 years’ experience in data engineering required.
• 2+ years of experience with Databricks and related technologies (Azure Data Factory, MS SQL Server, etc.).
• 2+ years’ experience in the financial services industry preferred.
• Certificate in SQL BI/EDW preferred.

Qualifications/Skills and Competencies:

• Advanced proficiency in Databricks, SQL, Python, and distributed data processing (e.g., Spark, Kafka).
• Strong ability in designing data models and working with cloud platforms (e.g., AWS, Azure, GCP).
• Strong understanding of insurance data domains: policy, claims, billing, reinsurance, and regulatory reporting.
• Familiarity with data governance, privacy, and compliance standards (e.g., NAIC, GDPR).
• Effective research, problem solving, analytical, critical thinking, influencing, and relationship management skills necessary.
• Ability to excel in a fast-paced environment.
• Excellent interpersonal skills with the ability to professionally interact with team members across departments.
• Strong written and verbal communication skills with the ability to professionally interact with team members in other departments.
• Exceptional time management skills with ability to prioritize tasks and allocate resources efficiently.
• Proven ability to be adaptable and flexible; able to adjust to new requirements or unforeseen issues.
• Proficient in MSO/365 applications such as Microsoft Teams, SharePoint, Word, Excel, PowerPoint, and Outlook.
• Desire to live Slide’s Core Values.

SLIDE INSURANCE - FUN. INNOVATION DRIVEN. FUELED BY PASSION, PURPOSE AND TECHNOLOGY.

At Slide, you will not only be part of a successful team, but you will also be a part of our Slide Vibe/award winning culture where collaboration and innovation are expected, recognized and awarded!

WHAT YOU WILL BE DOING:

• Design, develop, and optimize robust ETL/ELT pipelines for ingesting data from internal systems (policy, claims, billing) and external sources when applicable.
• Evaluate and integrate emerging technologies and tools to improve data engineering capabilities and performance.
• Design and manage modern data platforms (e.g., cloud-based data lakes or warehouses) to support real-time and batch processing use cases.
• Ensure data quality, integrity, and lineage by implementing rigorous validation and monitoring frameworks.
• Collaborate with data scientists, analysts, and business stakeholders to translate insurance-specific needs into scalable data solutions.
• Support data governance efforts by developing and maintaining documentation, metadata, and data dictionaries.
• Monitor individual and team performance, providing ongoing feedback and coaching to continuously improve results.
• Mentor junior engineers and contribute to setting data engineering best practices across the organization.
• Serve as the primary liaison between business and IT to ensure quality data and alignment.
• Perform other duties as assigned.