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

Amgen

Engineer II

Thousand Oaks, CA · On-site +1

$102K - $117K/yr

Career Category Engineering Join Amgen's Mission of Serving Patients At Amgen, if you feel like you ... Flexible work models, including remote and hybrid work arrangements, where possible Apply now and ...

Amgen, Inc.

Sr Machine Learning Engineer

Thousand Oaks, CA · On-site +1

$109K - $150K/yr

Senior Machine Learning Engineer What you will do Let's do this. Let's change the world. In this ... Flexible work models, including remote and hybrid work arrangements, where possible Apply now and ...

AppFolio, Inc.

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site +1

$116K - $159K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

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All JobsIntegration Engineer JobsRemote Integration Engineer JobsRemote Integration Engineer Jobs in Oxnard, CA

Remote Integration Engineer information

See Oxnard, CA salary details

$47.1K

$131.6K

$183.7K

How much do remote integration engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for remote integration engineer in Oxnard, CA is $131,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,100.00 and $148,300.00 per year, depending on experience, location, and employer.

What is a remote integration engineer?

A Remote Integration Engineer is responsible for connecting software systems, APIs, and databases to ensure seamless data flow and functionality across platforms. They work remotely to develop, troubleshoot, and maintain integrations between different applications, often using cloud-based services. Their role requires expertise in programming, APIs, and system architecture to optimize automation and interoperability. Additionally, they collaborate with development teams, product managers, and clients to meet business needs.

What does a remote integration engineer do?

A Remote Integration Engineer typically spends their days designing, developing, and maintaining integrations between different software systems and platforms. This often involves working with APIs, troubleshooting data transfer issues, and collaborating with other engineering or client teams to understand technical requirements. Additionally, you may participate in remote meetings, document integration processes, and provide support during deployments. The role requires balancing independent hands-on technical tasks with regular communication to ensure solutions align with business needs and project goals.

What are the key skills and qualifications needed to thrive as a remote integration engineer?

To excel as a Remote Integration Engineer, you need strong problem-solving skills, experience with API integration, and a solid background in computer science or a related field. Familiarity with integration platforms (like MuleSoft or Dell Boomi), scripting languages (such as Python or JavaScript), and certifications in cloud technologies or specific integration tools are highly valued. Excellent remote communication, time management, and collaboration skills help you coordinate effectively with distributed teams and clients. These skills are vital for delivering seamless, reliable integration solutions across different systems while working independently in a remote environment.

What are popular job titles related to Remote Integration Engineer jobs in Oxnard, CA? For Remote Integration Engineer jobs in Oxnard, CA, the most frequently searched job titles are:
What cities near Oxnard, CA are hiring for Remote Integration Engineer jobs? Cities near Oxnard, CA with the most Remote Integration Engineer job openings:
Remote Integration Engineer jobs near you
Infographic showing various Remote Integration Engineer job openings in Oxnard, CA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $131,605 per year, or $63.3 per hour.

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-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.

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