Senior Data Engineering Manager/Coach

Speridian Technologies; Sacramento (CA); Remote; USD 180,000 - 240,000; Full time

Job summary

Speridian Technologies is seeking a Data Engineering Manager for the California DHCS program. This remote, long-term consulting role involves leading a 10-20 person data engineering team, owning platform architecture, and delivering enterprise-scale data solutions that enable real-time analytics and govern data quality.

You will partner with analytics, data science, and product teams to drive ROI, cost optimization, and data governance while expanding the data platform at scale within a

Qualifications

• Proven track record managing data engineering teams of 20+ members.
• Experience owning P&L or budget responsibility for data platforms or products.
• Demonstrated ability to connect data infrastructure to business outcomes and ROI.
• Experience building and operating production data platforms at scale.
• Strong background in modern data engineering practices and cloud data technologies.
• Demonstrated ability to make architectural decisions for data systems and pipelines.
• Experience with full data lifecycle from ingestion through consumption.
• Track record of developing data engineers and building strong data engineering cultures.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.

Responsibilities

• Lead data platform leadership and architecture across enterprise systems.
• Own business metrics and ROI for data platform investments and initiatives.
• Manage a team of 10-20 data engineers; conduct regular career discussions.
• Establish data quality, governance, and monitoring standards.
• Collaborate with Analytics, Data Science, BI, and Product teams on roadmap.
• Lead hiring, mentoring, and building an inclusive, high-performing culture.

Skills

Data engineering leadership

Budget ownership

ROI analytics

Production data platforms

Spark & streaming

Cloud data technologies

Architectural decisions

Full data lifecycle

Team development

Education

Bachelor's degree in Computer Science/Engineering

Tools

Snowflake

Databricks

BigQuery

Redshift

Airflow

dbt

Kafka

Apache Spark

Python

SQL

Scala

Job description

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 roleRemote Role- USA, with some travel- about 10% to Sacramento for key meetingsWorking hours are Monday-Friday, PSTCommitment:

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 & Architecture
  • Drive data platform strategy and architecture decisions for enterprise data systems
  • Design and oversee data pipelines, warehouses, and lake architectures
  • Champion data engineering best practices including data quality, governance, and documentation
  • Make critical technical trade-off decisions balancing data freshness, accuracy, and infrastructure costs

  Outcome: Teams deliver scalable data platforms that enable analytics and data-driven decision making

• 2. Business Ownership & Financial Accountability
  • Own business metrics and ROI for data platform investments and initiatives
  • Develop and track cost-benefit analyses for data infrastructure and tooling decisions
  • Manage team budget including cloud data costs, tooling, and infrastructure spend
  • Translate data engineering work into business value and analytical capabilities for stakeholders
  • Drive efficiency improvements in data processing costs while maintaining data quality

  Outcome: Data engineering decisions driven by business value with clear ROI and financial accountability

• 3. People Management & Development
  • Manage, mentor, and develop a team of 10-20 data engineers
  • Conduct regular 1:1s focused on career development and performance
  • Execute performance management including promotions, improvement plans, and difficult conversations
  • Build diverse, inclusive teams through thoughtful hiring and team composition

  Outcome: High-performing teams with strong retention, clear growth paths, and engaged data engineers

• 4. Data Engineering Excellence & Quality
  • Establish and maintain standards for data quality, pipeline reliability, and monitoring
  • Drive continuous improvement in ETL/ELT practices and data tooling
  • Ensure appropriate data governance, security, and compliance implementation
  • Implement metrics and monitoring for data pipeline performance and data quality

  Outcome: Consistent delivery of reliable, high-quality data products with minimal pipeline failures

• 5. Cross-functional Partnership
  • Partner with Analytics, Data Science, and Business Intelligence teams on requirements
  • Collaborate with Product Management on data product roadmap and prioritization
  • Work with Software Engineering teams on application data integration
  • Communicate data architecture concepts and trade-offs to non-technical stakeholders

  Outcome: Strong partnerships enabling data democratization and self-service analytics

• 6. Talent Strategy & Team Building
  • Lead technical interviews and hiring decisions for data engineering roles
  • Develop team skills through mentoring, training, and stretch assignments
  • Identify and cultivate future data platform leaders
  • Build team culture emphasizing data quality, automation, and continuous learning

  Outcome: Strong talent pipeline with data engineers growing into senior and leadership roles

Required Qualifications

• Proven track record managing data engineering teams of 20+ members
• Experience owning P&L or budget responsibility for data platforms or products
• Demonstrated ability to connect data infrastructure to business outcomes and ROI
• Experience building and operating production data platforms at scale
• Strong background in modern data engineering practices and cloud data technologies
• Demonstrated ability to make architectural decisions for data systems and pipelines
• Experience with full data lifecycle from ingestion through consumption
• Track record of developing data engineers and building strong data engineering cultures
• Bachelor's degree in Computer Science, Engineering, or equivalent experience

Technical

Data Platforms:

• Snowflake, Databricks, BigQuery, Redshift, or similar

Data Processing:

• Apache Spark, Airflow, dbt, Kafka, streaming architectures

Cloud & Infrastructure:

• AWS/Azure/GCP data services and infrastructure as code

Data Modeling:

• Dimensional modeling, data vault, data mesh principles

Languages:

• SQL, Python, Scala, and data-specific programming paradigms

Business & Financial

Financial Management:

• Cloud data cost optimization, budget ownership, and ROI analysis

Business Metrics:

• Defining and tracking data platform KPIs and usage metrics

Value Communication:

• Articulating data investments in business terms

Resource Planning:

• Capacity planning for data workloads and storage

Vendor Management:

• Evaluating and managing data tools and platform services

Leadership

People Management:

• Performance management, career development, and difficult conversations
• Hiring, onboarding, and creating inclusive team environments

Communication:

• Technical and non-technical stakeholder management

Decision Making:

• Data-driven decisions balancing multiple constraints

Strategic Thinking:

• Aligning data platform efforts with organizational goals

Change Management:

• Leading teams through platform migrations and tool adoptions

General

Problem-Solving:

• Complex data and organizational challenge resolution

Collaboration:

• Working effectively with Analytics, Data Science, and Engineering functions

Mentorship:

• Developing junior and senior data engineers

Process Improvement:

• Identifying and implementing efficiency improvements

Business 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 Technology

Speridian 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.