Data Engineer

Job Description Insight Global is seeking a Data Engineer to sit hybrid in Frisco, Texas at a cybersecurity client. You will be responsible for designing, building, and overseeing the deployment and operation of technology architecture, solutions, and software that unlock the full potential of our data assets. This role combines hands-on technical implementation with strategic problem-solving to drive data-driven innovation across the organization. (This role can pay from $130,000

• $155,000 depending on years of experience).

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 HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

• 8+ years of hands-on experience in developing ETL/ELT pipelines across varied data sources, with demonstrated ability to work across the full spectrum of data engineering challenges
• Experience with Copilot and Claude Anthropic models to enhance development speed, code quality, and documentation
• Python, Scala, or Java, with ability to write production-quality code
• Experience with Snowflake, Databricks, Apache Spark, Kafka, Airflow)
• Practical knowledge of Model Context Protocol (MCP) to connect enterprise applications and automate data workflows
• Experience with cloud platforms (AWS, Azure, GCP) and their native data services
• Knowledge of containerization and orchestration technologies (Docker, Kubernetes)
• Strong expertise in data integration, transformation, and curation with a focus on quality and consistency
• Experience in client-facing or Professional Services roles