Database Engineer

Company Overview

At Enlyte, we combine innovative technology, clinical expertise, and human compassion to help people recover after workplace injuries or auto accidents. We support their journey back to health and wellness through our industry-leading solutions and services. Whether you're supporting a Fortune 500 client or a local business, developing cutting-edge technology, or providing clinical services you'll work alongside dedicated professionals who share your commitment to excellence and make a meaningful impact. Join us in fueling our mission to protect dreams and restore lives, while building your career in an environment that values collaboration, innovation, and personal growth.

Be part of a team that makes a real difference.

Job Description

As a Data Engineer in the Casualty Analytics Group, you will build and maintain the data infrastructure that powers Enlyte’s analytics and decision-making capabilities. You’ll join a growing engineering team and be responsible for developing robust data pipelines that integrate data from multiple source systems into our Snowflake data warehouse, ensuring data quality, reliability, and accessibility for downstream analytics. You'll have the opportunity to take on increasing ownership as the team and platform mature

Key Responsibilities:

Build and maintain production data pipelines using Snowflake and dbt to integrate and transform data from various sources (e.g. SQL Server, Oracle, PostgreSQL, Salesforce)

Implement data models and transformations following established architectural patterns and team standards

Collaborate with business stakeholders and senior engineers to understand data requirements and deliver high-value integrations

Write and maintain documentation for pipelines, data models, and engineering processes

Contribute to data governance and quality practices, including testing, monitoring, and alerting

Participate in code reviews, both giving and receiving feedback to maintain pipeline quality

Build proof-of-concepts and MVPs that demonstrate value for larger data initiatives

Qualifications

3-5 years of hands-on experience building data pipelines in production cloud environments

Strong proficiency in SQL, including performance tuning and window functions

Working knowledge of Python for data pipeline development and automation

Experience with modern data stack technologies including Snowflake, dbt, data ingestion tools (e.g. Snowflake Openflow, Fivetran), orchestration tools (e.g. Dagster, Airflow), AI-assisted development (e.g. Snowflake CoCo, GitHub CoPilot)

Familiarity with OLTP databases (e.g. PostgreSQL, Oracle, SQL Server), with understanding of the differences between OLTP and OLAP systems

Experience working with AWS cloud services for data workloads (S3 or similar)

Familiarity with CI/CD concepts and version control workflows (e.g. Git, pull requests, automated testing)

Strong communication skills with the ability to explain technical work to non-technical stakeholders

Proactive and self-motivated, comfortable working in a fast-paced environment with evolving priorities

Preferred Skills:

Bachelor’s degree in Computer Science, Data Engineering, or a related technical field

Experience with Medallion Architecture

Experience with using containerization technologies such as Docker and Kubernetes to deploy and manage data applications

Experience with analytics platforms like Hex and/or BI tools such as Power BI or Tableau

Understanding of the insurance industry, particularly workers' compensation or P&C insurance

Benefits

We’re committed to supporting your ultimate well-being through our total compensation package offerings that support your health, wealth and self. These offerings include Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts, Life and AD&D Insurance, 401(k), Tuition Reimbursement, and an array of resources that encourage a lifetime of healthier living. Benefits eligibility may differ depending on full-time or part-time status. Compensation depends on the applicable US geographic market. The expected base pay for this position ranges from $34.46 - $55.28 hourly, and will be based on a number of additional factors including skills, experience, and education.

The Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

Don’t meet every single requirement? Studies have shown that women and underrepresented minorities are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

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As a Data Engineer in the Casualty Analytics Group, you will build and maintain the data infrastructure that powers Enlyte’s analytics and decision-making capabilities. You’ll join a growing engineering team and be responsible for developing robust data pipelines that integrate data from multiple source systems into our Snowflake data warehouse, ensuring data quality, reliability, and accessibility for downstream analytics. You'll have the opportunity to take on increasing ownership as the team and platform mature

Key Responsibilities:

Build and maintain production data pipelines using Snowflake and dbt to integrate and transform data from various sources (e.g. SQL Server, Oracle, PostgreSQL, Salesforce)

Implement data models and transformations following established architectural patterns and team standards

Collaborate with business stakeholders and senior engineers to understand data requirements and deliver high-value integrations

Write and maintain documentation for pipelines, data models, and engineering processes

Contribute to data governance and quality practices, including testing, monitoring, and alerting

Participate in code reviews, both giving and receiving feedback to maintain pipeline quality

Build proof-of-concepts and MVPs that demonstrate value for larger data initiatives

3-5 years of hands-on experience building data pipelines in production cloud environments

Strong proficiency in SQL, including performance tuning and window functions

Working knowledge of Python for data pipeline development and automation

Experience with modern data stack technologies including Snowflake, dbt, data ingestion tools (e.g. Snowflake Openflow, Fivetran), orchestration tools (e.g. Dagster, Airflow), AI-assisted development (e.g. Snowflake CoCo, GitHub CoPilot)

Familiarity with OLTP databases (e.g. PostgreSQL, Oracle, SQL Server), with understanding of the differences between OLTP and OLAP systems

Experience working with AWS cloud services for data workloads (S3 or similar)

Familiarity with CI/CD concepts and version control workflows (e.g. Git, pull requests, automated testing)

Strong communication skills with the ability to explain technical work to non-technical stakeholders

Proactive and self-motivated, comfortable working in a fast-paced environment with evolving priorities

Preferred Skills:

Bachelor’s degree in Computer Science, Data Engineering, or a related technical field

Experience with Medallion Architecture

Experience with using containerization technologies such as Docker and Kubernetes to deploy and manage data applications

Experience with analytics platforms like Hex and/or BI tools such as Power BI or Tableau

Understanding of the insurance industry, particularly workers' compensation or P&C insurance