Data Engineer

Job Description

Experienced Full Stack Data Engineer with a strong focus on building, deploying, and supporting data‑driven applications. Brings hands-on experience leveraging Databricks as a core component of modern data lake architectures, enabling scalable data ingestion, transformation, and analytics across cloud environments. Adept at translating user-defined requirements into production-ready solutions that integrate tightly with enterprise data platforms. Targeting an hourly rate of $57-60/hr

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Core Strengths

• Strong communicator with the ability to collaborate across R&D, data, and application teams

• Highly independent problem-solver; capable of researching, designing, and implementing solutions with minimal oversight

• Comfortable operating across application development, cloud infrastructure, and data platforms

Data & Platform Expertise (Databricks + Data Lakes)

• Experience working with Databricks to support data lake architectures, enabling scalable processing of structured and semi-structured data

• Familiar with integrating Databricks workloads with cloud-based storage layers (e.g., object storage) to support analytics, reporting, and downstream applications

• Strong SQL knowledge applied to large datasets for querying, transformation, and validation

• Experience interfacing with multiple data products across R&D environments

Backend, Cloud & DevOps

• Backend Development: Proficient in Python, with a strong understanding of authentication and authorization workflows

• Cloud Technologies: Extensive experience with AWS services including IAM, CloudFormation, S3, Batch, Fargate, Lambda, and ECR

• CI/CD & Deployment: Working knowledge of CI/CD pipelines to support reliable application and data platform deployments

• Containers: Experience operating in containerized environments using Docker

• Front-End & Modern Web

○ Familiar with modern front-end technologies including React, ES6, Webpack, and modern JavaScript

Able to collaborate effectively with front-end teams to support data-driven user experiences