Data Engineering Manager

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineering Manager/Coach based in United States.

• Define data platform strategy and make architecture decisions across enterprise data systems, pipelines, warehouses, and lake architectures.
• Design and oversee scalable batch and real-time data solutions while balancing freshness, accuracy, reliability, performance, and infrastructure costs.
• Establish engineering standards for data quality, governance, documentation, monitoring, security, and compliance.
• Own platform budgets, cloud data costs, tooling investments, resource planning, and ROI analysis for data initiatives.
• Translate data engineering investments into measurable business value and communicate technical trade-offs clearly to stakeholders.
• Manage, mentor, and develop a team of approximately 10–20+ data engineers through regular coaching, career planning, performance management, hiring, and succession development.
• Build an inclusive, collaborative engineering culture centered on automation, data quality, continuous learning, and technical excellence.
• Partner with Analytics, Data Science, Business Intelligence, Product Management, and Software Engineering teams to define requirements and prioritize data products.
• Lead technical interviews, hiring decisions, onboarding, skills development, and stretch assignments to strengthen the team's long-term capabilities.
• Drive continuous improvement across ETL/ELT processes, platform tooling, data reliability, pipeline performance, and operational efficiency.
• Support platform migrations and technology adoption while guiding teams through organizational and technical change.

• Proven experience managing large data engineering teams, ideally 20+ members.
• Experience owning budgets, P&L responsibilities, or financial accountability for data platforms or technology products.
• Demonstrated ability to connect data infrastructure investments with business outcomes, KPIs, and ROI.
• Experience building and operating production-scale data platforms across the full data lifecycle, from ingestion through consumption.
• Strong understanding of modern data engineering practices, cloud data technologies, data architecture, governance, and quality management.
• Experience making architectural decisions involving data pipelines, platforms, warehouses, lakes, and streaming systems.
• Hands-on knowledge of platforms such as Snowflake, Databricks, BigQuery, Redshift, or comparable technologies.
• Experience with Apache Spark, Airflow, dbt, Kafka, and real-time or streaming architectures.
• Familiarity with AWS, Azure, or GCP data services and infrastructure-as-code practices.
• Strong understanding of data modeling approaches such as dimensional modeling, data vault, and data mesh principles.
• Proficiency with SQL, Python, Scala, or comparable data-focused programming technologies.
• Strong financial and operational skills, including cloud cost optimization, capacity planning, vendor evaluation, and resource management.
• Excellent communication skills with the ability to explain technical architecture and investment decisions in clear business terms.
• Demonstrated success in performance management, career development, hiring, team building, and difficult conversations.
• Strong strategic thinking, problem-solving, decision-making, collaboration, mentorship, and change-management capabilities.
• A consulting mindset, high ownership, curiosity, and motivation to solve complex organizational and technical challenges.
• Bachelor's degree in Computer Science, Engineering, or equivalent professional experience.
• Must be authorized to work in the United States; visa sponsorship or transfer is not available for this role.
• Ability to work Monday through Friday on Pacific Time and travel to Sacramento approximately 10% of the time.

• Fully remote position within the United States.
• Full-time, long-term consulting engagement.
• Opportunity to work on large-scale healthcare data transformation with significant public-sector impact.
• Choice of engagement structure, including W2 employment or 1099/independent contractor arrangements.