Lead Data Engineer

Lead Data Engineer

We're hiring for a full-time Lead Data Engineer in Seattle, WA. This role will require 2-3 days onsite/week in Seattle - as such, only local candidates will be considered at this time. Architect and build scalable, reliable data pipelines and processes that transform raw operational and external data into curated datasets for analytics and BI. Model data using open table formats and warehouse schemas, enforcing contracts, SLAs, quality checks, and lineage tracking. Define and implement sustainable, repeatable data transformation and storage strategies with advanced analytics in mind. Establish best practices for data observability, monitoring, governance, and compliance to ensure consistency, reliability, and regulatory alignment. Lead technical design reviews, code reviews, and documentation to uphold engineering quality, reliability, and maintainability. Identify bottlenecks, propose scalable solutions, and contribute to the technical roadmap while mentoring engineers to expand team capacity. Evaluate and adopt new tools, frameworks, and methodologies that improve scalability, robustness, and productivity. Drive delivery using Agile and DevOps practices; ensure smooth deployments, incident response, and ongoing maintenance. Contribute to organizational knowledge by maintaining clear technical documentation, design records, and deployment guides.

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.

Skills and Requirements:

• 5+ years' experience in data engineering, with 2+ years in a lead/senior/principal role (driving technical direction and mentoring junior engineers).
• Demonstrated success leading design and delivery of large-scale, mission-critical data platforms in production.
• Hands-on experience with cloud-native data platforms (AWS) and orchestration at scale (Kubernetes/EKS).
• Experience establishing engineering best practices in CI/CD, containerization, observability, security, and data governance.
• Deep experience building and optimizing modern Lakehouse solutions using open table/catalog formats (Apache Iceberg, Project Nessie), Parquet, and query engines such as Presto/Trino.
• Strong SQL expertise for designing, optimizing, and troubleshooting complex analytical queries across large, diverse datasets.
• Strong background in data modeling, integration, and governance/compliance, with the ability to evolve schemas, enforce data contracts, and maintain reliability at scale.
• Proven expertise architecting and operating large-scale ETL/ELT pipelines, with advanced proficiency in Apache Spark (PySpark) and strong programming skills in Python and Java or Scala.
• Strong stakeholder management skills, ability to influence roadmaps and align technical initiatives with business priorities.
• Relevant certifications (i.e.: AWS Data Analytics, Kubernetes Administrator, Databricks/Snowflake).