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Data Structure Jobs in California (NOW HIRING)

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Responsibilities : • Develop and maintain a comprehensive understanding of Abaka AI's dataset library, including data structure, quality, and applicable use cases across modalities (text, image ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Responsibilities : • Develop and maintain a comprehensive understanding of Abaka AI's dataset library, including data structure, quality, and applicable use cases across modalities (text, image ...

Canopy A&D

ERP Data Analyst

Riverside, CA

$150K - $175K/yr

Serve as a subject matter expert for Epicor ERP data structures, system architecture, tables, and core business processes, ensuring alignment with operational workflows. * Maintain and proactively ...

Canopy A&D

ERP Data Analyst

Riverside, CA · On-site

$150K - $175K/yr

Serve as a subject matter expert for Epicor ERP data structures, system architecture, tables, and core business processes, ensuring alignment with operational workflows. * Maintain and proactively ...

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All JobsData Structure JobsData Structure Jobs in California

Data Structure information

See California salary details

$45.4K

$162.9K

$240.3K

How much do data structure jobs pay per year?

As of Jun 13, 2026, the average yearly pay for data structure in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What profession makes $400,000 a year?

In the field of data structures, senior software engineers, data architects, and machine learning engineers with extensive experience and advanced skills can earn salaries around $400,000 annually, especially in high-cost living areas or large tech companies. These roles typically require strong programming skills, knowledge of algorithms, and often advanced degrees or certifications. Compensation varies based on location, company size, and individual expertise.

What are data structures?

Data structures are specialized formats for organizing, processing, and storing data in computers so that it can be accessed and modified efficiently. Common types include arrays, linked lists, stacks, queues, trees, and graphs. Each data structure is designed to solve specific types of problems and optimize certain operations such as searching, sorting, or inserting data. Understanding data structures is fundamental for programming and software development, as they directly impact the performance and scalability of applications.

What is the difference between Data Structure vs Data Analyst?

AspectData StructureData Analyst
Required CredentialsComputer Science degree, programming skillsStatistics, data analysis certifications, degree in related fields
Work EnvironmentSoftware development, programming, algorithm designBusiness, finance, marketing, data interpretation
Industry UsageSoftware engineering, computer scienceBusiness intelligence, marketing, finance

Data Structures focus on organizing and storing data efficiently within software applications, requiring programming skills and technical knowledge. Data Analysts interpret data to provide insights, often using statistical tools and working closely with business teams. While Data Structures are foundational for software development, Data Analysts apply data to solve business problems. Both roles are essential in data-driven industries but serve different purposes and skill sets.

What is a Data Structure job?

A Data Structure job typically involves designing, implementing, and optimizing data storage and retrieval mechanisms in software applications. Professionals in this role work with different data structures like arrays, linked lists, trees, and graphs to improve the efficiency of algorithms. They are often employed in software development, data engineering, or system architecture roles, ensuring that data is managed efficiently for various applications. Strong problem-solving skills and proficiency in programming languages like Python, Java, or C++ are essential for success in this field.

What engineers make $500,000?

Senior software engineers, especially those working in high-demand areas like technology, finance, or specialized fields such as machine learning or cybersecurity, can earn $500,000 or more annually. Achieving this level typically requires extensive experience, advanced skills, and often stock options or bonuses in addition to base salary.

What jobs use data structures?

Data structures are fundamental in many jobs related to software development, such as software engineers, data analysts, and database administrators. These roles require understanding and implementing data structures like arrays, trees, and graphs to optimize algorithms and manage data efficiently.

What are the key skills and qualifications needed to thrive as a Data Structures Engineer, and why are they important?

To thrive as a Data Structures Engineer, you need a solid understanding of algorithms, programming languages (such as Java, C++, or Python), and a formal education in computer science or a related field. Familiarity with version control systems like Git, debugging tools, and experience with relevant libraries or frameworks are typically required. Strong analytical thinking, problem-solving abilities, and effective communication help you design efficient solutions and collaborate with other developers. These skills ensure robust, scalable software that meets performance requirements and supports business objectives.

What is a data structure job?

A data structure job involves designing, implementing, and maintaining data structures that organize and store data efficiently for software applications. These roles often require knowledge of algorithms, programming languages like Python or C++, and problem-solving skills to optimize data handling and performance.

What are some common challenges faced by professionals working with data structures in software development?

Professionals working with data structures often encounter challenges such as selecting the most efficient data structure for a specific application, optimizing memory usage, and ensuring code scalability as data volume grows. Collaboration with other team members, such as developers and data engineers, is essential to design robust solutions that balance performance and maintainability. Additionally, staying current with evolving algorithms and best practices helps address complex data manipulation tasks in real-world projects.
What are the most commonly searched types of Data Structure jobs in California? The most popular types of Data Structure jobs in California are:
What are popular job titles related to Data Structure jobs in California? For Data Structure jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Structure jobs in California look for? The top searched job categories for Data Structure jobs in California are:
Data Structure jobs near you

Data Entry & QMS Data Migration Specialist (Structured Data & System Implementation)

Biolegacy Research

San Diego, CA • On-site

$25 - $27/hr

Temporary

Posted 11 days ago

Job description

Type: 6 months with extension to 12 or conversion

Location: Headquarters – Sorrento Valley, San Diego, CA

Work Type: Onsite

Pay Range: $25 - $27

Department: Quality Assurance

Reports To: Head of QA

Position Summary

We are seeking a highly detail-oriented Data Entry & QMS Data Migration Specialist to support the implementation of a new Quality Management System (QMS).

This role goes beyond basic data entry. The ideal candidate will be responsible for organizing, structuring, mapping, and standardizing large volumes of manual and legacy data into a clean, consistent, and usable format within a new software system.

You will play a critical role in transforming unstructured or inconsistent records into a well-organized, searchable, and audit-ready system. This position is ideal for someone who enjoys bringing order to complex information and working with structured processes in a regulated environment.

Key ResponsibilitiesData Entry & Structuring

Accurately enter data from spreadsheets, documents, and legacy systems into the new QMS platform

Standardize and organize data fields, naming conventions, and formats for consistency

Label, categorize, and structure records to ensure easy retrieval and system usability

Data Cleaning & Organization

Identify and correct inconsistencies, duplicates, and incomplete records

Consolidate and normalize data from multiple sources into a unified structure

Ensure data aligns with defined templates, formats, and QA standards

Data Mapping & Migration

Map data fields between legacy systems and the new QMS platform

Support data transformation and migration workflows, ensuring accurate field alignment

Validate migrated data and troubleshoot discrepancies

Quality Control & Validation

Perform detailed quality checks to ensure accuracy, completeness, and consistency

Reconcile migrated data against source records

Support User Acceptance Testing (UAT) to verify system functionality and data integrity

Documentation & Process Support

Document data structures, mapping logic, and migration processes

Track issues, resolutions, and updates for audit readiness

Support QA and project teams in maintaining compliant, audit-ready documentation

Cross-Functional Collaboration

Work closely with QA, IT, and project stakeholders

Provide input on improving data structure, workflows, and system usability

Support overall QMS implementation efforts

Qualifications

Required

High school diploma or equivalent

Proven experience in data entry, data organization, or data migration

Strong proficiency in Microsoft Excel (sorting, filtering, formatting, basic formulas)

Exceptional attention to detail and accuracy

Strong organizational and problem-solving skills

Ability to work with large volumes of structured and unstructured data

Preferred

Experience with QMS systems, document control systems, or regulated environments (biotech, pharma, healthcare)

Familiarity with data mapping, system implementation, or migration projects

Basic knowledge of databases, SQL, or ETL concepts

Experience supporting QA or compliance-driven teams

What We’re Looking For

Someone who enjoys organizing complex or messy data into clean, structured systems

Highly detail-oriented with a strong sense of data accuracy and consistency

Process-driven and comfortable working within defined standards and frameworks

Able to think beyond data entry and understand how data should be structured within a system

Work Environment

This is an onsite role based in a professional office setting. The position requires sustained focus, attention to detail, and working with large datasets and documentation in a structured, deadline-driven environment.

Equal Opportunity Employer

BioLegacy Research is an Equal Opportunity Employer. We are committed to building a diverse and inclusive workplace.

Apply