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Manager Data Analytics Engineer Jobs in Long Beach, CA

Design and manage automated data lifecycles using GitHub Actions and Terraform (Infrastructure as ... Provide oversight and mentorship to data engineers, analysts, and scientists, setting engineering ...

Design and manage automated data lifecycles using GitHub Actions and Terraform (Infrastructure as ... Provide oversight and mentorship to data engineers, analysts, and scientists, setting engineering ...

Design and manage automated data lifecycles using GitHub Actions and Terraform (Infrastructure as ... Provide oversight and mentorship to data engineers, analysts, and scientists, setting engineering ...

Partner closely with data engineering teams to design and improve scalable data pipelines, data ... analytics, CRM, marketing systems, and operational data * Contribute to improvements in data ...

Partner closely with data engineering teams to design and improve scalable data pipelines, data ... analytics, CRM, marketing systems, and operational data * Contribute to improvements in data ...

Partner closely with data engineering teams to design and improve scalable data pipelines, data ... analytics, CRM, marketing systems, and operational data * Contribute to improvements in data ...

Partner closely with data engineering teams to design and improve scalable data pipelines, data ... analytics, CRM, marketing systems, and operational data * Contribute to improvements in data ...

Manager, Data Analytics

Santa Monica, CA · On-site +1

$158K - $224K/yr

About the Manager, Data Analytics at Headspace: What you will do: * Drive significant business ... Provide thought leadership by collaborating with Product, Engineering, Marketing, and Operations to ...

Manager, Data Analytics

Santa Monica, CA · On-site

$158K - $224K/yr

About the Manager, Data Analytics at Headspace: What you will do: * Drive significant business ... Provide thought leadership by collaborating with Product, Engineering, Marketing, and Operations to ...

Responsibilities : • Manage the project and stakeholders through all core project phases ... programming languages • Ability to profile, explore, and analyze data to identify common data ...

Responsibilities : • Manage the project and stakeholders through all core project phases ... programming languages • Ability to profile, explore, and analyze data to identify common data ...

US is seeking an experienced Data & Analytics Manager to join our growing data practice. In this ... Bachelor's degree in engineering, information systems, computer science, business administration ...

US is seeking an experienced Data & Analytics Manager to join our growing data practice. In this ... Bachelor's degree in engineering, information systems, computer science, business administration ...

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Showing results 1-20

Manager Data Analytics Engineer information

See Long Beach, CA salary details

$46.8K

$136.4K

$186.6K

How much do manager data analytics engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for manager data analytics engineer in Long Beach, CA is $136,394.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,400.00 and $144,600.00 per year, depending on experience, location, and employer.

What is a manager data analytics engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.

How does a manager data analytics engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a manager data analytics engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

What are popular job titles related to Manager Data Analytics Engineer jobs in Long Beach, CA?

For Manager Data Analytics Engineer jobs in Long Beach, CA, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Long Beach, CA look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Long Beach, CA are:

What cities near Long Beach, CA are hiring for Manager Data Analytics Engineer jobs?

Cities near Long Beach, CA with the most Manager Data Analytics Engineer job openings:

Data/Analytics Engineer

Heluna Health

Los Angeles, CA • On-site

Full-time

Re-posted 18 days ago


Job description

Salary Range: $10,214.43 -$13.376.56 monthly

SUMMARY

Serves as the Data & Analytics Engineer for Community Programs (CPs), acting as the Lead Data Architect for CP’s Databricks environment. This role sits at the intersection of data engineering and advanced analytics, responsible for the end-to-end design, implementation, and management of a governed Medallion Architecture (Bronze, Silver, Gold) supporting housing, justice, and clinical operations. This position replaces legacy reporting workflows with a unified, secure data platform that stitches complex, multi-sector program participation records across disparate systems into a cohesive longitudinal client model. The role bridges infrastructure and advanced analytics by building scalable data products and integrations that support program tracking, executive reporting, and predictive modeling for County and State stakeholders.

WHAT YOU WILL DO

  • Build and scale a governed Databricks environment that serves as the single source of truth across housing, justice, and clinical systems
  • Design and implement automated, production-grade data pipelines and CI/CD workflows using Databricks, Terraform, and GitHub
  • Translate complex program logic into scalable data models and reusable data products
  • Build scalable semantic models that map a single client's journey across disparate housing, justice, and clinical programs, standardizing touchpoints over time.
  • Establish secure-by-design data systems handling sensitive clinical (PHI) and justice (CJI) data utilizing Unity Catalog for centralized governance, audit logging, and access control.
  • Enable advanced analytics by developing curated datasets, APIs, and environments for machine learning and NLP applications
  • Partner with leadership and cross-functional teams to shape how data is used to drive policy, operations, and outcomes
  • Lead and mentor technical staff while setting engineering standards for long-term scalability and maintainability
  • Programmatically map complex, multi-source program utilization (CHAMP, DD, HMIS) to specific funding streams for strict fiscal and grant tracking compliance.

ESSENTIAL FUNCTIONS

  • Data Infrastructure & Lakehouse Architecture: Design, implement, and maintain a scalable Databricks architecture using Medallion principles. Build and optimize large-scale ETL/ELT pipelines to integrate structured and unstructured data across housing, justice, and clinical systems. Ensure interoperability with healthcare and justice standards (e.g., FHIR, HL7v2) and support a unified, governed data environment serving as the system of record for analytics.
  • Infrastructure Automation & DevOps (CI/CD): Design and manage automated data lifecycles using GitHub Actions and Terraform (Infrastructure as Code). Implement software engineering practices, including version control, automated unit testing, and continuous integration to validate pipeline logic prior to production deployment.
  • Data Modeling & Technical Translation: Design and maintain the Unified Data Model for Community Programs, serving as the foundation for the entire analytical schema. Lead architectural efforts to model and stitch together complex, multi-sector longitudinal client journeys across CHAMP, DD, HMIS, and various systems. Develop specialized, multi-dimensional data structures that accurately map cross-program utilization to diverse, overlapping funding streams, enabling precise fiscal, operational, and programmatic evaluation.
  • Data Governance, Security & Compliance: Establish and enforce enterprise data governance frameworks, including RBAC/ABAC, data lineage, audit logging, and data loss prevention. Ensure security, compliance, and data integrity are embedded across all layers of the architecture, supporting high-trust environments handling regulated data (e.g., PHI, CJI).
  • Analytics Enablement & Data Products: Develop and manage scalable data products, including curated datasets, APIs, and analytical layers that support reporting, dashboards, and advanced analytics. Optimize data access and performance using SQL and modern BI tools (e.g., Tableau, Power BI), enabling consistent, reliable insights for operational and executive decision-making.
  • Technical Leadership & Delivery Oversight: Provide oversight and mentorship to data engineers, analysts, and scientists, setting engineering standards and promoting best practices in system design.
  • Advanced Analytics Support & Integration: Build and maintain the technical environments required for advanced analytics. Partner with data scientists and DHS Security teams to ensure models and data products are scalable, governed, and aligned with transparency and compliance standards.

JOB QUALIFICATIONS

  • Candidates must possess substantial experience in Enterprise Data Architecture, Cloud Infrastructure, and Analytics Engineering. Candidates must hold a relevant degree and demonstrate a proven track record of managing complex data lifecycles within large-scale Databricks environments.
  • Substantial experience in Cloud Data Engineering and Infrastructure Automation.
  • Preferred:
    • Experience with public sector / healthcare / justice data is a plus
    • Experience working with regulated data (HIPAA, CJIS) is a plus
    • Experience in cross-agency data integration is a plus
  • Education: Relevant degree from an accredited college or university.

Education/Experience

Option I: Two (2) years of experience in a lead capacity carrying out complex data infrastructure and architecture projects. This must include independently designing and implementing automated ETL/ELT pipelines, managing Lakehouse environments (Databricks), and enforcing enterprise data security (RBAC/ABAC), at a level equivalent to the Los Angeles County class of Principal Information Systems Analyst.

Option II: A Bachelor’s degree from an accredited college or university in a field of applied research such as Information Technology, Computer Science, Data Engineering, or Data Science —AND— six (6) years of experience applying and overseeing the application of data engineering, infrastructure automation (CI/CD), and enterprise data management to support operational and analytical decision making. Two (2) years of this experience must have been in a lead capacity.

For Option II only, a Master’s or Doctoral degree from an accredited college or university in a field such as Information Technology, Computer Science, Data Science, or Machine Learning may substitute for up to two (2) years of the required general experience.

  • Applicants must meet the above requirement(s) at the time of filing to be appointed to fill any vacancies related to this recruitment.
  • ACCREDITATION: Accredited institutions are those listed in the publications of regional, national or international accrediting agencies which are accepted by the Department of Human Resources
  • Foreign degrees must be evaluated for equivalency to United States accredited institutions standards by an academic credential evaluation agency recognized by The National Association of Credential Evaluation Services (NACES) or The Association of International Credential Evaluators, Inc. (AICE)

Certificates/Licenses/Clearances

  • Successfully pass DHS Live Scan

Other Skills, Knowledge, and Abilities

  • Expert Proficiency in Python: Focused on data manipulation (Pandas/PySpark) and automation.
  • Expert Proficiency in SQL: Deep knowledge of query optimization, CTEs, and window functions.
  • Advanced Data Visualization: Proven ability to build executive-level insights in Tableau or Power BI.
  • Cloud Automation: Hands-on experience with Terraform and GitHub Actions.

SELECTION PROCESS

  • Live Technical Interview: Shortlisted candidates will participate in a live technical assessment. This session will evaluate proficiency in SQL/Python, architectural problem-solving within the Databricks ecosystem, and the ability to translate programmatic logic into scalable data models.

PHYSICAL DEMANDS

Stand: Occasionally

Walk: Occasionally

Sit: Frequently

Handling / Fingering: Frequently

Reach Outward: Occasionally

Reach Above Shoulder: Occasionally

Climb, Crawl, Kneel, Bend: Occasionally

Lift / Carry: Occasionally - Up to 25 lbs

Push/Pull: Occasionally - Up to 25 lbs

See: Constantly

Taste/ Smell: Not Applicable

Not Applicable = Not required for essential functions

Occasionally = (0 - 2 hrs/day)

Frequently = (2 - 5 hrs/day)

Constantly = (5+ hrs/day)

 

WORK ENVIRONMENT

General Office Setting, Indoors Temperature Controlled

EEOC STATEMENT

It is the policy of Heluna Health to provide equal employment opportunities to all employees and applicants, without regard to age (40 and over), national origin or ancestry, race, color, religion, sex, gender, sexual orientation, pregnancy or perceived pregnancy, reproductive health decision making, physical or mental disability, medical condition (including cancer or a record or history of cancer), AIDS or HIV, genetic information or characteristics, veteran status or military service.