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Manager Data Analytics Engineer Jobs in California

Company Description We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems ...

Company Description We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems ...

We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems and the Hadoop stack.

We are seeking a developer to join the data analytics team with at least 12 years of software development experience. The candidate must have experience with distributed systems and the Hadoop stack.

We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems and the Hadoop stack.

We are seeking a developer to join the data analytics team with at least 12 years of software development experience. The candidate must have experience with distributed systems and the Hadoop stack.

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Manager Data Analytics Engineer information

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.

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 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.
What are the most commonly searched types of Data Analytics Engineer jobs in California? The most popular types of Data Analytics Engineer jobs in California are:
What are popular job titles related to Manager Data Analytics Engineer jobs in California? For Manager Data Analytics Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in California look for? The top searched job categories for Manager Data Analytics Engineer jobs in California are:
What cities in California are hiring for Manager Data Analytics Engineer jobs? Cities in California with the most Manager Data Analytics Engineer job openings:
Data Analytics & Engineering Program Manager

Data Analytics & Engineering Program Manager

Pinkerton

Santa Clara, CA

$149K/yr

Full-time

Posted 2 days ago


Pinkerton rating

9.6

Company rating: 9.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

2nd of 100 rated security


Job description

Overview

170+ Years Strong. Industry Leader. Global Impact.
At Pinkerton, the mission is to protect our clients. To do this, we provide enterprise risk management services and programs specifically designed for each client. Pinkerton employees are one of our most important assets and critical to the delivery of world-class solutions. Bonded together, we share a commitment to integrity, vigilance, and excellence.

Pinkerton is an inclusive employer who seeks candidates with diverse backgrounds, experiences, and perspectives to join our network of industry subject matter experts.

The Data Analytics & Engineering Program Manager, assigned to a specific client, will lead and manage the Physical Security Data Analytics and Engineering Program, including driving the design, implementation, and optimization of data analytics strategies and engineering solutions. The Manager ensures operational excellence by managing critical data policies, tools, and frameworks while collaborating with cross-functional team to support organizational objectives through actionable insights, enhanced physical security systems, and innovative data solutions.


Responsibilities

  • Represent Pinkerton’s core values of integrity, vigilance, and excellence.
  • Lead and manage the physical security data analytics and engineering program.
  • Develop and execute project plans, timelines, and budgets.
  • Coordinate with cross-functional teams to ensure project objectives are met.
  • Oversee the collection, analysis, and interpretation of security data to identify trends, risks, and areas for improvement.
  • Develop and maintain security dashboards and reporting tools for real-time monitoring and decision-making.
  • Design and implement engineering solutions to enhance physical security systems including access control, surveillance, and intrusion detection systems.
  • Ensure all security systems are integrated, scalable, and compliant with industry standards.
  • Develop, implement, and maintain policies, procedures, and best practices for data analytics and engineering initiatives.
  • Collaborate with stakeholders to gather requirements and translate business needs into technical solutions.
  • Oversee the design and deployment of data pipelines, ensuring data accuracy, consistency, and accessibility.
  • Manage and optimize data architecture, storage solutions, and cloud-based platforms to support scalable operations.
  • Track, monitor, and report key performance indicators (KPIs) for data projects, providing actionable insights to stakeholders.
  • Identify and resolve data-related issues, escalating complex challenges to relevant teams.
  • Lead the development and delivery of training programs to enhance data literacy and tool adoption across the organization.
  • Schedule and facilitate project meetings while ensuring clear communication, accurate documentation, and timely follow-ups.
  • Conduct routine audits of data systems and processes to ensure compliance with organizational and regulatory standards.
  • Collaborate with cross-functional teams to integrate data solutions into broader organizational workflows.
  • Stay updated on emerging trends in data analytics and engineering while recommending tools and technologies to improve efficiency.
  • Serve as a subject matter expert and trusted advisor for data-driven decision making.
  • All other duties, as assigned.

Qualifications

Bachelor’s degree in data science, computer science, engineering, or a related field with ten years of experience managing data analytics and engineering programs including the development of scalable data solutions.

  • AWS Certified Data Analytics, Microsoft Certified Azure Data Engineer Associate or Google Professional Data Engineer certifications, preferred.
  • Knowledge designing and implementing physical security systems including access control, surveillance, and intrusion detection.
  • Proficient in physical security engineering and system integration.
  • Advanced knowledge of machine learning frameworks and statistical modeling.
  • Able to analyze complex data sets and develop actionable insights.
  • Familiar with regulatory and compliance standards for data management and security.
  • Able to interact effectively at all levels and across diverse cultures.
  • Able to lead cross-functional teams and manage multiple projects simultaneously.
  • Attentive to detail and accuracy.
  • Effective written and verbal communication skills with the ability to present complex data insights clearly.
  • Serve as a positive team leader.
  • Client orientated and results driven.
  • Proficient with big data tools and technologies such as Hadoop, Spark.
  • Computer skills; Microsoft Office, Snowflake, SQL, and Python.

Working Conditions:

With or without reasonable accommodation, requires the physical and mental capacity to effectively perform all essential functions;

  • Regular computer usage.
  • Occasional reaching and lifting of small objects and operating office equipment.
  • Frequent sitting.
  • Travel, as required.

Pinkerton is an equal opportunity employer to all applicants and positions without regard to race/ethnicity, color, national origin, ancestry, sex/gender, gender identity/expression, sexual orientation, marital/prenatal status, pregnancy/childbirth or related conditions, religion, creed, age, disability, genetic information, veteran status, or any protected status by local, state, federal or country-specific law.