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Remote Data Engineer Jobs in Riverview, FL (NOW HIRING)

micro1 AI

Senior Database Reliability Engineer

Tampa, FL · Remote

$220K - $260K/yr

Senior Database Reliability Engineer: Job Type: Full-time Location: Remote Job Summary: Join our ... remote team. Preferred Qualifications: • Experience supporting data platforms, analytics ...

AgileEngine

Full Stack Engineer ID80989

Tampa, FL · On-site +1

... data, and collaborate closely with product, QA, and design teams in an Agile environment. This is a US-based, remote-friendly contract-to-hire opportunity for high-performing engineers. WHAT YOU WILL ...

Bond-Pro Inc

Senior Software Engineer (Remote)

Tampa, FL · Remote

$125K - $165K/yr

Contribute to big data architecture and design patterns batch and/or streaming pipelines, data ... Mentor junior developers through code review, pairing, and design discussions. Required ...

PRESHai

Product Engineer

Tampa, FL · On-site +1

$115K - $150K/yr

Own product capabilities across retrieval, memory, data pipelines, evals, observability, and human ... Ability to work from our downtown Tampa office four days per week, with one remote day. Helpful ...

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · On-site +1

$98K - $135K/yr

Retrieval & Data: PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis * Infra: AWS, Kubernetes ... All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town ...

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All JobsData Engineer JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Riverview, FL

Remote Data Engineer information

See Riverview, FL salary details

$39.7K

$115.7K

$158.3K

How much do remote data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote data engineer in Riverview, FL is $115,696.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,100.00 and $122,600.00 per year, depending on experience, location, and employer.

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 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 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.

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 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.

Are remote data engineers still in demand?

Remote data engineers are currently in high demand due to the increasing reliance on data-driven decision making and cloud-based data platforms. Skills in SQL, Python, cloud services, and data pipeline tools are highly sought after, and many organizations continue to hire for remote roles to access a broader talent pool.

Can a remote data engineer work remotely?

Yes, remote data engineers can work remotely, as the role primarily involves managing data pipelines, databases, and cloud-based tools that can be accessed from anywhere with an internet connection. Many companies offer remote positions for data engineers, often requiring skills in SQL, Python, cloud platforms, and data architecture. However, some roles may require occasional on-site presence or specific certifications depending on the employer's policies.
More about Remote Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Riverview, FL?

The most popular types of Data Engineer jobs in Riverview, FL are:

What are popular job titles related to Remote Data Engineer jobs in Riverview, FL?

For Remote Data Engineer jobs in Riverview, FL, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineer jobs in Riverview, FL look for?

The top searched job categories for Remote Data Engineer jobs in Riverview, FL are:

What cities near Riverview, FL are hiring for Remote Data Engineer jobs?

Cities near Riverview, FL with the most Remote Data Engineer job openings:

Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Riverview, FL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $115,696 per year, or $55.6 per hour.

Director of Data Center

Imagine Staffing Technology

Saint Petersburg, FL • Remote

$170K - $200K/yr

Full-time

Re-posted 28 days ago

Job description

Job Title: Director of Data Strategy and Services
Location: St. Petersburg, FL
Hire Type: Direct Hire
Pay Range: $170,000 - $200,000 
Work Type: Full-time 
Work Model: Remote 
Work Schedule: Monday – Friday, 8am – 5pm 
Recruiter Contact: Sean Pebbles | 716.256.1259 | spebbles@imaginegroup.com
 
Nature & Scope:
Positional Overview
 
The Imagine Group is recruiting for a Director of Data Strategy and Services on behalf of our client, a leading provider of cloud-based software solutions that empower nonprofit organizations, associations, educational institutions, and mission-driven businesses to streamline operations and strengthen community engagement in St. Petersburg, FL. Through innovative technology and a customer-focused approach, the organization helps clients manage fundraising, membership, events, and financial processes while driving meaningful impact.
 
In this role you will be responsible for leading the strategic direction, daily operations, and performance of data center infrastructure to ensure the availability, security, and reliability of critical business systems. You will oversee capacity planning, disaster recovery, vendor relationships, and infrastructure projects while partnering with cross-functional teams to optimize operational efficiency, maintain compliance, and support long-term technology initiatives.
 
Role & Responsibility:
Tasks That Will Lead to Your Success
 
  • Enterprise Data Architecture & Strategy 
  • Architecture Ownership: Own, evolve, and scale the enterprise data architecture supporting all product verticals. 
  • Operational Standards: Establish standards, best practices, and repeatable patterns for data ingestion, transformation, and consumption. 
  • Roadmap Alignment: Align data strategy directly with internal product roadmaps, engineering timelines, and advanced client analytics needs. 
  • Planning & Design: * Define data migration scopes, constraints, historical requirements, and success criteria. 
  • Design data mapping, transformation, enrichment, validation, and rollback protocols. 
  • Partner with stakeholders to establish testing cycles, cutover plans, and client approvals. 
  • Execution & Delivery: Oversee extraction, transformation, and loading (ETL) into test, UAT, and production environments. 
  • Lead iterative migration cycles, resolve technical anomalies, and manage post-migration hypercare/remediation. 
  • Deliver comprehensive migration completion documentation and client sign-offs. 
  • Data Readiness: Assess source data usability; cleanse, normalize, and de-duplicate data sets to make them analytics-ready. 
  • Custom Analytics & BI: Translate complex business objectives into custom dashboards, defining metrics, visualizations, filters, and refresh cadences. 
  • Strategy Consulting: Advise clients on data collection methodologies (timing, frequency, automation) and practical data governance/stewardship operating frameworks. 
  • Help define, manage, and mature the delivery workflows and quality standards associated with the Company’s AI Analytics subscription service offerings. 
  • Prescriptive Analytics: Operationalize benchmarking frameworks and peer-group analysis, translating data into executive-ready insights for priority customer segments. 
  • Service Commercialization: Track measurable client outcomes to develop case studies; partner with Product, Marketing, and Sales to support go-to-market and thought-leadership activities. 
  • Integration Roadmap: Scope, prioritize, and support deal-driven integrations with third-party platforms to enhance workflow analytics. 
  • Agentic Capabilities: Contribute to the creation, refinement, and client-facing alignment of agentic roles and AI-enabled capabilities. 
  • Org Design: Build out the core Data Strategy & Services operating models, documentation standards, and prioritization frameworks. 
  • Legacy Continuity: Maintain high-level Project Manager/Customer Engagement continuity for designated legacy accounts (requirements definition, risk management, internal coordination) during the initial transition framework. 
  • Lead the creation and execution of cross-functional and cross-product data best practices.  
  • Create and maintain Data COE Playbooks: Recommended operating models, prioritization frameworks, and service definitions for the scaled Data Strategy organization. 
  • Create and maintain Technical Checklists: Robust service packages, data migration roadmaps, governance documentation, and architectural mapping guides. 
  • Revenue in alignment with commercial targets.  
  • Team billable utilization equal to or greater than goal.