Sr. Data Engineer (Databricks)

Job Description The data engineer will be focused on building and optimizing scalable data pipelines, data models, and database designs that support analytics and operational use cases. The ideal candidate is a high‑throughput, senior‑level data engineer who can ramp effectively, work within full CI/CD governance, and contribute at or above squad productivity once up to speed. 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 5-7+ years of experience as a data engineer with:

• Strong, hands‑on experience with Databricks (critical, primary platform)
• Apache Spark for large‑scale data processing
• Advanced Python and SQL (performance tuning and complex transformations)
• DBT for data modeling and pipeline development
• Experience designing and maintaining robust data pipelines
• Experience working under full CI/CD governance
• Source control using GitHub
• AWS exposure, including sourcing data from S3
• Familiarity with Airflow
• Conceptual knowledge of tools such as Monte Carlo or Atlan
• Experience supporting data quality, observability, or governance initiatives
• Exposure to media, ad tech, or large‑scale enterprise data
• Experience optimizing both batch and real‑time data workflows