Data Engineer

We are seeking a Mid-Level Data Engineer to design, build, and maintain data pipelines and infrastructure that power analytics, reporting, and data-driven decision-making. You'll collaborate with product, data analysts, and software engineers to ensure our data ecosystem is reliable, scalable, and efficient.
• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data from customer applications, third-party sources, public websites, APIs, and internal systems.
• Leverage AI/ML models and web scraping frameworks to extract, clean, and normalize structured and unstructured data for integration into core pipelines and monetized datasets.
• Develop intelligent data enrichment workflows using AI/ML techniques (e.g., entity resolution, anomaly detection, and NLP-based parsing).
• Implement and optimize data models and architectures to support analytics, reporting, and monetization strategies.
• Write and optimize SQL queries and other data transformations for performance at scale.
• Ensure data quality, reliability, and consistency by applying validation frameworks, automated testing, and observability tools.
• Monitor pipelines and AI models for accuracy, data drift, performance, and data freshness-proactively addressing issues and driving continuous improvements.
• Collaborate cross-functionally with analysts, engineers, and data scientists to deliver high-quality, reliable data products.
• Implement monitoring and observability for pipeline health, usage metrics, and operational reliability.
• Document technical specifications, workflows, and integrations to support maintainability and knowledge sharing.
• Participate in peer code reviews, contributing constructive feedback and adhering to best practices.
• Ensure compliance with data security, privacy, and governance requirements (e.g., NIST, StateRAMP, FedRAMP, GDPR) in all data pipelines and monetized data products.

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.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Required Skills & Experience
• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering or equivalent role.
• Proficient in SQL, with demonstrated experience in query tuning and optimization.
• Strong programming skills in Python (C#, Java, or Scala a plus).
• Experience with ETL orchestration tools (Glue, Apache Airflow, Talend, ADF, Databricks).
• Familiarity with cloud data platforms (Snowflake, Redshift, Synapse).
• Understanding of best practices in data modeling and warehousing.
• Exposure to data lake or lakehouse architectures.
• Experience with version control (Git).
• Experience with BI tools (Power BI, Tableau).
• Familiarity with real-time data streaming (Kafka, Kinesis, Azure Event Hubs, Redpanda).

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.