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Remote Data Optimization Jobs in California (NOW HIRING)

Innowhyte Inc

Ensure data pipelines are optimized for efficiency, reliability, and scalability, handling both structured and unstructured data seamlessly. Handle large-scale datasets, ensuring data integrity and ...

Innowhyte Inc

... optimized for efficiency, reliability, and scalability, handling both structured and unstructured data seamlessly. • Handle large-scale datasets, ensuring data integrity and consistency across ...

Sedgwick

Data Engineer AI

Los Angeles, CA · On-site +1

$123K - $148K/yr

Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

York Risk Services

Data Engineer AI

Los Angeles, CA · On-site +1

$123K - $148K/yr

Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Lever Demo 2

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ... Monitor and assess marketing inbound efforts (SEO, natural & paid search, content) Help growth ...

thatgamecompany

Senior Data Analyst

Los Angeles, CA · Remote

$109K - $171K/yr

Remote US & Canada We are seeking a highly motivated and autonomous Senior Data Analyst to join our ... Extensive experience writing optimized SQL to build and analyze datasets and associated data ...

Corvel

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and analyze data from internal databases to drive optimization and improvement of product development and ...

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Remote Data Optimization information

What is a Remote Data Optimization specialist?

A Remote Data Optimization specialist is a professional who works remotely to analyze, refine, and improve data systems and processes for organizations. Their main goal is to enhance the efficiency, accuracy, and usability of data, often by cleaning datasets, streamlining data flows, and implementing best practices for data management. They may use various tools and techniques to ensure data integrity and improve how data is stored, accessed, and utilized. These specialists often collaborate with data analysts, engineers, and business teams to support data-driven decision-making.

What is a data optimization job example?

A data optimization job involves analyzing and improving data quality, structure, and storage to enhance efficiency and accuracy. For example, optimizing database queries or cleaning large datasets using tools like SQL or Python helps organizations make better data-driven decisions.

What is the highest paying job in data?

In data-related fields, roles such as Chief Data Officer, Data Science Director, and Machine Learning Engineer tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with relevant certifications and experience.

What are some common challenges faced by professionals in remote data optimization roles, and how can they be addressed?

Remote data optimization professionals often encounter challenges such as coordinating with distributed teams, ensuring data accuracy across different systems, and managing time effectively without in-person supervision. To address these, it's important to establish clear communication channels, use collaborative tools for data sharing and project tracking, and set regular check-ins with team members. Additionally, staying updated on best practices and automation tools can help streamline workflows and enhance data quality, making remote work more efficient and productive.

Is it possible to get a remote job as a data analyst?

Yes, remote data analyst positions are widely available across various industries. These roles typically require skills in data analysis tools like Excel, SQL, or Python, and often involve working with cloud-based platforms or collaboration tools. Many companies offer remote work options for data analysts, especially with experience in data visualization and reporting.

Is 40 too late for data science?

Remote Data Optimization roles often value skills and experience over age, and many professionals transition into data science later in their careers. Learning relevant tools like Python, SQL, and machine learning can help, and continuous education or certifications can improve job prospects regardless of age.

What are the key skills and qualifications needed to thrive as a Remote Data Optimization Specialist, and why are they important?

To excel as a Remote Data Optimization Specialist, you need a solid background in data analysis, strong proficiency in statistics, and experience with optimization techniques, typically supported by a degree in data science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau or Power BI), programming languages (such as Python or R), and database systems is commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills set top performers apart in this role. These competencies are vital for translating complex data into actionable insights and driving efficiency improvements from a remote environment.

What is the difference between Remote Data Optimization vs Remote Data Analyst?

AspectRemote Data OptimizationRemote Data Analyst
Primary FocusImproving data storage, retrieval, and processing efficiencyAnalyzing data to identify trends and generate reports
Required SkillsData management, database tuning, scriptingData analysis, visualization, statistical skills
CertificationsDatabase certifications, data management credentialsData analysis certifications, SQL proficiency
Work EnvironmentTechnical teams, IT departments, data warehousesBusiness units, marketing, finance teams

Remote Data Optimization specialists focus on enhancing data systems' performance, while Remote Data Analysts interpret data to support decision-making. Both roles require strong technical skills, but their core responsibilities differ significantly, making them distinct career paths within data management and analysis.

What are the most commonly searched types of Data Optimization jobs in California? The most popular types of Data Optimization jobs in California are:
What are popular job titles related to Remote Data Optimization jobs in California? For Remote Data Optimization jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Data Optimization jobs in California look for? The top searched job categories for Remote Data Optimization jobs in California are:
What cities in California are hiring for Remote Data Optimization jobs? Cities in California with the most Remote Data Optimization job openings:
Remote Data Optimization jobs near you
Infographic showing various Remote Data Optimization job openings in California as of June 2026, with employment types broken down into 50% Full Time, 25% Part Time, and 25% Contract. Highlights an 100% Remote job distribution.
Sr. Software Engineer, Big Data, tvScientific

Sr. Software Engineer, Big Data, tvScientific

Pinterest

San Francisco, CA • Remote

$65.75 - $87/hr

Other

Posted 6 days ago

Job description

About tvScientific

tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.

As a Senior Data Engineer at tvScientific, you will be a key player in implementing the robust data infrastructure to power our data-heavy company. You will collaborate with our cross-functional teams to evolve our core data pipelines, design for efficiency as we scale, and store data in optimal engines and formats. This is an individual contributor role, where you will work to define and implement a strategic vision for data engineering within the organization. 


What you'll do:

  • Implement robust data infrastructure in AWS, using Spark with Scala
  • Evolve our core data pipelines to efficiently scale for our massive growth
  • Store data in optimal engines and formats
  • Collaborate with our cross-functional teams to design data solutions that meet business needs
  • Built out fault-tolerant batch and streaming pipelines
  • Leverage and optimize AWS resources while designing for scale
  • Collaborate closely with our Data Science and Product teams
  • How we'll define success:
    • Successful implementation of scalable and efficient data infrastructure
    • Timely delivery and optimization of data assets and APIs
    • High attention to detail in implementation of automated data quality checks
    • Effective collaboration with cross-functional teams


What we're looking for:

  • Production data engineering experience
  • Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
  • Familiarity with data lakes, cloud warehouses, and storage formats
  • Strong proficiency in AWS services
  • Expertise in SQL for data manipulation and extraction
  • Excellent written and verbal communication skills
  • Bachelor's degree in Computer Science or a related field
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
  • Nice-to-Haves
    • Experience in adtech
    • Experience implementing data governance practices, including data quality, metadata management, and access controls
    • Strong understanding of privacy-by-design principles and handling of sensitive or regulated data
    • Familiarity with data table formats like Apache Iceberg, Delta

In-Office Requirement Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.


Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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