Senior Data Engineering Manager/Coach

Job Title: Data Engineering Manager, Data Platform – Behavioral Health Transformation Location: Remote (Working hours are Monday-Friday PST) Division: Medical Enterprise System Modernization Division (MESMD) Department: California Department of Health Care Services (DHCS) Must work on shore in the US. We cannot sponsor or transfer an H1B Visa for this role Remote Role- USA, with some travel- about 10% to Sacramento for key meetings Working hours are Monday-Friday, PST Commitment: Full-Time Consultant to DHCS; you can work with us two ways: as a W2 employee of Speridian OR a 1099/IC/LLC. This is a long-term contract Speridian has with DHCS. We are in year three of a three-year contract with two two-year extensions. Ready to democratize data for California's healthcare revolution? Join the Department of Healthcare Services (DHCS) as a Data Engineering Manager, where you'll architect the data platforms that power evidence-based decisions affecting 16 million Californians' healthcare journeys. As a Data Engineering Manager, you'll lead a team of data engineering experts building enterprise-scale data platforms that transform petabytes of healthcare information into actionable insights. This role goes beyond traditional ETL pipelines – you'll design real-time streaming architectures, implement advanced analytics capabilities, and create self-service data products that empower teams across the organization. Your data platforms will enable predictive analytics that prevent fraud, optimize care delivery, and literally save lives through better healthcare outcomes. DHCS offers the rare opportunity to work with healthcare data at a scale that rivals major tech companies, while directly improving public health. You'll have full ownership of the data platform strategy, invest in modern tools like Databricks and Snowflake, and the mandate to build a world-class data engineering organization. Our commitment to data-driven transformation means your work will be highly visible and directly tied to the department's strategic objectives. We're looking for a data platform visionary who understands that great data engineering enables great decisions – someone who can optimize Spark jobs while evangelizing data literacy, who treats data quality as sacred, and who believes government should lead in leveraging data for public good. Responsibilities & Outcomes 1. Data Platform Leadership & ArchitectureDrive data platform strategy and architecture decisions for enterprise data systemsDesign and oversee data pipelines, warehouses, and lake architecturesChampion data engineering best practices including data quality, governance, and documentationMake critical technical trade-off decisions balancing data freshness, accuracy, and infrastructure costsOutcome: Teams deliver scalable data platforms that enable analytics and data-driven decision making 2. Business Ownership & Financial AccountabilityOwn business metrics and ROI for data platform investments and initiativesDevelop and track cost-benefit analyses for data infrastructure and tooling decisionsManage team budget including cloud data costs, tooling, and infrastructure spendTranslate data engineering work into business value and analytical capabilities for stakeholdersDrive efficiency improvements in data processing costs while maintaining data qualityOutcome: Data engineering decisions driven by business value with clear ROI and financial accountability 3. People Management & DevelopmentManage, mentor, and develop a team of 10-20 data engineersConduct regular 1:1s focused on career development and performanceExecute performance management including promotions, improvement plans, and difficult conversationsBuild diverse, inclusive teams through thoughtful hiring and team compositionOutcome: High-performing teams with strong retention, clear growth paths, and engaged data engineers 4. Data Engineering Excellence & QualityEstablish and maintain standards for data quality, pipeline reliability, and monitoringDrive continuous improvement in ETL/ELT practices and data toolingEnsure appropriate data governance, security, and compliance implementationImplement metrics and monitoring for data pipeline performance and data qualityOutcome: Consistent delivery of reliable, high-quality data products with minimal pipeline failures 5. Cross-functional PartnershipPartner with Analytics, Data Science, and Business Intelligence teams on requirementsCollaborate with Product Management on data product roadmap and prioritizationWork with Software Engineering teams on application data integrationCommunicate data architecture concepts and trade-offs to non-technical stakeholdersOutcome: Strong partnerships enabling data democratization and self-service analytics 6. Talent Strategy & Team BuildingLead technical interviews and hiring decisions for data engineering rolesDevelop team skills through mentoring, training, and stretch assignmentsIdentify and cultivate future data platform leadersBuild team culture emphasizing data quality, automation, and continuous learningOutcome: Strong talent pipeline with data engineers growing into senior and leadership roles Required QualificationsProven track record managing data engineering teams of 20+ membersExperience owning P&L or budget responsibility for data platforms or productsDemonstrated ability to connect data infrastructure to business outcomes and ROIExperience building and operating production data platforms at scaleStrong background in modern data engineering practices and cloud data technologiesDemonstrated ability to make architectural decisions for data systems and pipelinesExperience with full data lifecycle from ingestion through consumptionTrack record of developing data engineers and building strong data engineering culturesBachelor's degree in Computer Science, Engineering, or equivalent experienceTechnicalData Platforms: Snowflake, Databricks, BigQuery, Redshift, or similarData Processing: Apache Spark, Airflow, dbt, Kafka, streaming architecturesCloud & Infrastructure: AWS/Azure/GCP data services and infrastructure as codeData Modeling: Dimensional modeling, data vault, data mesh principlesLanguages: SQL, Python, Scala, and data-specific programming paradigmsBusiness & FinancialFinancial Management: Cloud data cost optimization, budget ownership, and ROI analysisBusiness Metrics: Defining and tracking data platform KPIs and usage metricsValue Communication: Articulating data investments in business termsResource Planning: Capacity planning for data workloads and storageVendor Management: Evaluating and managing data tools and platform servicesLeadershipPeople Management: Performance management, career development, and difficult conversationsTeam Building: Hiring, onboarding, and creating inclusive team environmentsCommunication: Technical and non-technical stakeholder managementDecision Making: Data-driven decisions balancing multiple constraintsStrategic Thinking: Aligning data platform efforts with organizational goalsChange Management: Leading teams through platform migrations and tool adoptionsGeneralProblem-Solving: Complex data and organizational challenge resolutionCollaboration: Working effectively with Analytics, Data Science, and Engineering functionsMentorship: Developing junior and senior data engineersProcess Improvement: Identifying and implementing efficiency improvementsBusiness Acumen: Understanding business context and impact of data platform decisions What Sets Top Performers Apart Success in this role goes beyond compensation, work-life balance, or a typical corporate career mindset. We’ve found that intrinsic motivation—a genuine drive to grow, solve complex problems, and create lasting impact—is a defining trait of those who truly thrive here. We’re looking for individuals with a consulting mindset, a passion for technology, and above all, a deep personal commitment to delivering meaningful results. This environment is fast-paced and demanding—we hold ourselves to high standards every day. This role isn't for everyone, and we’re honest about that. But for those motivated by purpose, challenge, and the chance to lead with impact, it could be the ideal next step in your career. Interview Process: Recruiter Call and then:Take-home project (1 hour) 1 hour (Take Home Review, People Management, Culture & Communication)1 hour (Technical, Design) 45 minutes (Executive & Critical Thinking) Statement for Speridian TechnologySperidian Technology is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Reasonable accommodations are available for qualified individuals with disabilities during the application process.