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Remote Data Engineer Jobs in Oxnard, CA (NOW HIRING)

Saransh Inc

Salesforce Engineer

Woodland Hills, CA · Remote

$56.75 - $75.25/hr

Atlanta, GA / Woodland Hills, CA (3 days a week onsite is required) / Remote also fine Job Type ... Data Modeling specific to Salesforce * Must have strong hands-on experience in OmniStudio ...

Amgen, Inc.

Sr Machine Learning Engineer

Thousand Oaks, CA · On-site +1

$109K - $150K/yr

Collaborate with data scientists to develop, train, and evaluate machine learning models. * Build ... Flexible work models, including remote and hybrid work arrangements, where possible Apply now and ...

DataAnnotation

SDLC Engineer - AI Trainer

Oxnard, CA · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... Experience with algorithms, data structures, and debugging workflows * A current, in progress, or ...

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All JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Oxnard, CA

Remote Data Engineer information

See Oxnard, CA salary details

$47.1K

$137.4K

$188K

How much do remote data engineer jobs pay per year?

As of Jul 6, 2026, the average yearly pay for remote data engineer in Oxnard, CA is $137,367.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,300.00 and $145,600.00 per year, depending on experience, location, and employer.

What Does a Remote Data Engineer Do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

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

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote Data Engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a Remote Data Engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

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

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.
More about Remote Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Oxnard, CA? The most popular types of Data Engineer jobs in Oxnard, CA are:
What are popular job titles related to Remote Data Engineer jobs in Oxnard, CA? For Remote Data Engineer jobs in Oxnard, CA, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Oxnard, CA look for? The top searched job categories for Remote Data Engineer jobs in Oxnard, CA are:
What cities near Oxnard, CA are hiring for Remote Data Engineer jobs? Cities near Oxnard, CA with the most Remote Data Engineer job openings:
Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Oxnard, CA as of June 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $137,367 per year, or $66 per hour.
Real Estate Data Scientist - Remote

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago

Job description


The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy.
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development: No
  • Decision making:
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel: Up to 10%
  • Flex Designation: Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.
Requirements
Education and Experience
Education Requirements
  • Bachelor's degree in data science, Statistics, Economics, Mathematics, Computer Science, or related field from a nationally recognized institution. Master's degree preferred
Years of Experience
  • 5 to 8 plus years of experience in data science, analytics, or quantitative modeling, preferably in retail, real estate, consulting, or related fields.
Skills
  • Strong proficiency in Python (pandas, scikit-learn, etc.) and SQL for data analysis and modeling.
  • Experience building predictive models and applying statistical techniques to business problems.
  • Experience working with cloud-based platforms (Databricks, Snowflake, Azure)
  • Familiarity with geospatial analysis and GIS concepts, including trade area modeling, spatial statistics, and network-based analysis (experience with ESRI or similar tools preferred).
  • Experience working with large, complex datasets from multiple sources.
  • Experience with BI and visualization tools (Tableau, Power BI, etc.).
  • Strong understanding of experimental design and statistical inference.
  • Ability to communicate complex analyses clearly to non-technical stakeholders.
  • Strong problem-solving skills and business acumen.
Physical Requirements
Corporate - Remote - General office environment requiring ability to:
  • Stand, walk, sit for extended periods of time .
  • Speak and listen to others in person and over the phone and video conferencing.
  • Use keyboard and read from computer screen and reports.
  • The ability to lift up to 15 lbs.
Safety
Must be able to perform this job safely in accordance with standard operating procedures and good manufacturing practices, without endangering the health or safety of self or others.
About Harbor Freight Tools
We're a 45 year-old, $8 billion national tool retailer with the energy, enthusiasm, and growth potential of a start-up. We have over 1,600 stores in 48 states across the country and are opening several new locations every week. We offer our customers more than 7,000 tools and accessories, from hand tools and generators to air and power tools, from shop equipment to automotive tools. We provide our customers with the right tool for the right job at the right price, always delivering quality and value.

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