Data Engineer
Summary
Build and maintain scalable data pipelines using Databricks, GCP, and Azure to power AI models, RAG search, and enterprise analytics for a Fortune 500 company.
Data Engineer, AI Development
Hybrid opportunity: 2 days in the office, 3 days from home.
Insight at a Glance
- 14,000+ engaged teammates globally
- $8.2 billion in revenue in 2025
- Certified as a Great Place to Work in 9 countries in 2025
- Fortune 500 Company
- Received 25+ industry and partner awards in the past year
We are not just a tech company; we’re a people‑first company. With deep expertise in cloud, data, AI, cybersecurity, and intelligent edge, Insight guides organizations through complex digital decisions.
About the role
The Data Engineer is a key technical role on the AI Development team, responsible for building and maintaining the data pipelines that power our AI transformation and analytics initiatives. You will work with modern technologies like Databricks, GCP, and Azure to ensure our data is clean, reliable, and accessible for AI model training, RAG‑based search, and enterprise reporting. You will help bridge the gap between raw enterprise data and production‑ready AI solutions.
Responsibilities
- Build and maintain scalable ETL/ELT processes and data pipelines to ingest and transform data from various sources (ERP, CRM, e‑commerce) for use in AI agents and analytics.
- Support the maintenance and optimization of our Databricks‑based data lakehouse to ensure performance and reliability for data science and business intelligence needs.
- Implement data quality checks and monitoring to ensure the integrity of data assets used in AI applications and enterprise dashboards.
- Partner with AI developers and business stakeholders to prepare and optimize datasets for specific AI use cases and agentic workflows.
- Utilize the Databricks platform (including MCP and Feature Store) to prepare data for machine learning models and AI applications.
- Support data governance practices, including data lineage and security; help catalog and document data assets to make them discoverable for the team.
- Work with native cloud services on Azure and GCP to implement scalable data storage and compute solutions.
- Assist in modeling clean, reliable datasets to support Power BI reporting and business intelligence initiatives.
Be AmbITious: This opportunity is not just about what you do today but also about where you can go tomorrow. When you bring your hunger, heart, and harmony to Insight, your potential will be met with continuous opportunities to upskill, earn promotions, and elevate your career.
What we’re looking for
- Minimum 3 years of experience in data engineering, focusing on building and maintaining production data pipelines.
- Proficiency with Databricks for data engineering and lakehouse support, including PySpark and Databricks Workflows.
- Hands‑on experience with cloud data services in Microsoft Azure or GCP.
- Experience building and optimizing ETL/ELT processes and data transformation workflows.
- Proficient in Python and SQL; familiarity with Java or similar languages is a plus.
- Experience working with enterprise data tools (e.g., Informatica) and familiarity with data modeling for PowerBI.
- Good analytical and problem‑solving skills with a proactive approach to resolving data issues.
- Strong communication skills in English, with the ability to collaborate effectively in an Agile team environment.
- Bachelor’s degree in Computer Science, Engineering, or a related field.
What you can expect
- Freedom to work from another location—even an international destination—for up to 30 consecutive calendar days per year.
- HMO on Day1 with 2 free dependents.
Insight is an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation, or any other characteristic protected by law.