Data-DevOps Engineer - Hybrid (Flexible)

K2 Security Insurance•San Diego, CA

8h•Hybrid

About The Position

K2 Insurance Services, LLC is seeking a Data Engineer with a strong Azure DevOps focus to join their engineering team. This role will support the development, maintenance, and optimization of data solutions that enable business insights across the organization, while also playing an active role in owning and enhancing Azure DevOps–based CI/CD pipelines. The ideal candidate is an eager data professional with strong SQL skills, hands‑on experience with relational databases (preferably cloud‑based), and solid, practical experience working with Azure DevOps and modern cloud engineering practices. The successful candidate will work closely with data engineers, analysts, and business stakeholders to design and build reliable data pipelines, maintain data quality, and support analytics and reporting initiatives within the insurance domain, while also contributing to the development, maintenance, and continuous improvement of Azure DevOps–based CI/CD pipelines and deployment processes. This role will involve a mix of data engineering and Azure DevOps responsibilities, with opportunities to grow in both areas.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Engineering or a related field (or equivalent work experience).
Hands‑on experience with RDBMS platforms (cloud‑based preferred).
Strong SQL skills, including writing complex queries, joins, subqueries, CTEs, and performance‑optimized queries for relational databases.
Hands-on experience with Azure DevOps (or minimally GitHub), including building release pipelines, as well as build, test and deployment automation.
Experience working with Python in notebooks or scripts to support data engineering workflows.
Familiarity with Terraform and Infrastructure as Code (IaC) concepts, including understanding how infrastructure is defined and managed in code.
Strong communication and interpersonal skills.
Ability to work effectively in a fast-paced and collaborative environment.

Nice To Haves

Experience in the insurance industry.
Experience with agile methodologies and project management tools like Jira or DevOps.
Experience with Databricks.

Responsibilities

Develop, optimize, and maintain complex SQL queries, views, and python-based notebooks.
Build and support ELT data pipelines from structured and unstructured data sources.
Work with Databricks to source data from relational databases to store, retrieve, and transform data efficiently.
Collaborate with analysts and stakeholders to interpret business requirements, translate them into efficient data models, and build scalable SQL logic that supports analytics, reporting, and downstream consumption.
Support production workloads, including triaging failed jobs, root-cause analysis, and implementing long‑term stability improvements.
Use Azure DevOps for source control, build and release pipelines, and CI/CD workflows.
Maintain and expand Infrastructure as Code (IaC) to support consistent, repeatable environment provisioning and configuration (e.g., updates to templates/modules and environment definitions).
Contribute to the enhancement, optimization, and ongoing maintenance of existing CI/CD pipelines.
Support deployment and release processes across development and production environments.
Create, maintain, and update environment and release documentation, including deployment notes, pipeline changes, and release announcements.
Partner with data engineers and analysts to understand data requirements.
Document data and release pipelines, database structures, and operational processes.
Participate in agile ceremonies such as sprint planning and daily standups.
Ensure high‑quality delivery by following established engineering standards and contributing to the continuous improvement of workflows.
Contribute to knowledge sharing by updating internal documentation and code as systems evolve.
Assist with incident triage, troubleshooting, and post‑release validation under guidance from senior team members.