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Data Optimisation Jobs in California (NOW HIRING)

Apple

CapEx Data Optimization Product Manager

Sunnyvale, CA · On-site

$196K - $203K/yr

The Product Operations Data Team is looking for an analytically sharp, intellectually curious individual to own the data optimization vision for our Capex Equipment Engineering organization. This is ...

Amazon

Data Engineer II, Ring Agent Platforms

Hawthorne, CA · On-site

$116K - $139K/yr

This role will be expected to utilize GenAI to build reliable, scalable data pipelines, which produce data optimized for our customers, who will also be utilizing AI Agent pipelines. Key job ...

ITC Infotech (USA), Inc

Sr. Data Engineer

Sacramento, CA · On-site

$124K - $149K/yr

Enterprise Analytics & Reporting, Cloud Migration & Server Administration, SAP Enterprise Support, Protocol & Data Optimization, Global Study & Contract Analytics Professional Certification * Tableau ...

K2 Space

Senior Application Data Engineer

Los Angeles, CA · On-site

$114K - $155K/yr

... optimization, ensure data integrity and accuracy. • Evaluate and make decisions regarding competing data design tradeoffs. • Advocate, defend and convert other engineering leaders to your own ...

Tror AI for everyone

AI/ML Architect

Los Angeles, CA · On-site

$68.75 - $88.25/hr

Data partitioning, file size tuning, and optimization strategies for large-scale pipelines. * Experience handling multi-terabyte structured time‑series workloads. * Ability to distill architectural ...

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Data Optimisation information

What are the most common challenges faced in a data optimisation role, and how can I prepare for them?

One of the main challenges in a Data Optimisation role is dealing with large, complex datasets that may have inconsistencies or missing information. You’ll often need to balance improving data quality with maintaining data integrity and system performance. Collaborating across departments, such as IT, analytics, and business operations, is typical, so strong communication skills are essential. Preparing by learning best practices in data cleaning, ETL processes, and familiarizing yourself with relevant tools will help you succeed and adapt quickly.

What are the key skills and qualifications needed to thrive as a data optimisation specialist?

To thrive as a Data Optimisation Specialist, you need strong analytical skills, proficiency in data analysis, and a background in statistics or computer science, often supported by relevant degrees or certifications. Familiarity with data management tools like SQL, Python, Excel, and optimisation platforms such as Google Analytics or Tableau is typically required. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for translating insights into actionable strategies. These skills ensure that data-driven decisions are accurate, impactful, and aligned with business objectives.

What are data optimisation jobs?

Data optimisation jobs involve analyzing and improving data quality, structure, and efficiency to support better decision-making and operational performance. These roles often require skills in data analysis, database management, and tools like SQL or data visualization software, with a focus on enhancing data accuracy and accessibility.

What is data optimisation?

Data optimisation refers to the process of improving the quality, accessibility, and efficiency of data within an organization. It involves cleaning, structuring, and organizing data so that it can be used more effectively for analysis, decision-making, and business operations. Data optimisation can help reduce storage costs, enhance system performance, and ensure that accurate and relevant data is available when needed. This process often includes data deduplication, compression, and the implementation of best practices for data management.

What is the difference between Data Optimisation vs Data Analysis?

AspectData OptimisationData Analysis
Primary FocusImproving data processes and system efficiencyInterpreting data to uncover insights
Skills RequiredData management, process improvement, technical skillsStatistical analysis, reporting, critical thinking
Work EnvironmentIT teams, data engineering, system optimizationBusiness units, research teams, analytics departments
CertificationsData management, database certificationsData analysis, statistical certifications

Data Optimisation focuses on enhancing data systems and processes for efficiency, while Data Analysis involves examining data to generate insights. Both roles require strong technical skills, but their objectives differ: one improves data infrastructure, the other interprets data for decision-making.

What are popular job titles related to Data Optimisation jobs in California? For Data Optimisation jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Optimisation jobs in California look for? The top searched job categories for Data Optimisation jobs in California are:
What cities in California are hiring for Data Optimisation jobs? Cities in California with the most Data Optimisation job openings:
Data Optimisation jobs near you
Infographic showing various Data Optimisation job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

CapEx Data Optimization Product Manager

Apple

Sunnyvale, CA • On-site

$196K - $203K/yr

Full-time

Re-posted 13 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don't just create products - they create the kind of wonder that has revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it.
The Product Operations Data Team is looking for an analytically sharp, intellectually curious individual to own the data optimization vision for our Capex Equipment Engineering organization. This is not a model-building role - it is an architectural and strategic one. You will serve as the critical bridge between deep Capex domain knowledge and the technical capabilities of a dedicated ML engineering team, translating what the business needs to predict into what the models need to learn. This is a high-growth opportunity for a driven, curious individual who is ready to own something significant and expand their impact as the vision scales.
Description
In this role you will define, shape, and drive the data optimization frameworks that transform how the Capex team operates - shifting from manual estimation to model-driven prediction that influences product design decisions before commitments are made.
Minimum Qualifications
3+ years of experience in an analytical, data, or technically oriented role
BS or MS degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent hands-on experience
Strong quantitative analytical skills - comfortable working with complex, multi-source datasets to extract meaningful signals
Foundational understanding of how predictive models work - what they require as inputs, how they are trained, and how their outputs should be interpreted and validated
Demonstrated ability to translate ambiguous business problems into structured, precise requirements that a technical team can act on
Preferred Qualifications
5+ years of experience in an analytically driven role with increasing scope and ownership
Some exposure to manufacturing, supply chain, or capital equipment environments - enough to engage credibly with domain concepts and recognize when a model output makes operational sense
Experience working at the interface between business and engineering teams, serving as a translator or connector across functions
Familiarity with data pipeline concepts, feature engineering, and model validation practices - even without hands-on model building experience
Experience defining requirements for ML or data products and partnering with technical teams through the development lifecycle
Clear and confident communicator, able to represent team needs to a technical audience and explain complex analytical concepts to non-technical stakeholders
Demonstrated intellectual curiosity and a track record of growing technical depth independently in a fast-moving environment
Comfortable operating in ambiguous, early-stage problem spaces where the framework itself is still being defined

What Apple employees say

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Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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