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Remote Data Engineering Jobs in Oklahoma (NOW HIRING)

SmartLight Analytics

Senior Data Engineer

Tulsa, OK · Remote

$96K - $131K/yr

Partner with the existing SQL Server Data Engineering team to plan and execute the migration of ... Strong self-management skills with the ability to work independently in a fully remote environment.

SmartLight Analytics

Senior Data Engineer

Tulsa, OK · On-site +1

$96K - $131K/yr

Partner with the existing SQL Server Data Engineering team to plan and execute the migration of ... Strong self-management skills with the ability to work independently in a fully remote environment.

CCT

AWS Cloud Data Engineer

Tulsa, OK · On-site +1

$104K - $125K/yr

Minimum 5 years of applicable work experience within data engineering. * Strong analytical skills and the ability to translate data into actionable insights. * Excellent technical writing and oral ...

ONEOK, Inc

Engineer II (ILI Data Analysis)

Tulsa, OK · On-site +1

$104K - $125K/yr

While an Engineering degree is preferred, other applicable degrees such as Computer Science ... The schedule is Hybrid, working from the Tulsa office Monday-Thursday and working remote on Friday.

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All JobsData Engineering JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Oklahoma

Remote Data Engineering information

See Oklahoma salary details

$41.1K

$119.8K

$163.9K

How much do remote data engineering jobs pay per year?

As of Aug 3, 2026, the average yearly pay for remote data engineering in Oklahoma is $119,772.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $127,000.00 per year, depending on experience, location, and employer.

Can I work remotely as a data engineer?

Yes, remote data engineering roles are common, allowing professionals to work from various locations. These jobs often require skills in cloud platforms, programming, and data pipeline tools, and may involve collaboration through online communication tools.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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 (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives.

How to make $1000 a week remote?

Remote data engineers can earn $1000 or more per week by working on high-demand projects, leveraging specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL. Building a strong portfolio, obtaining relevant certifications, and working with multiple clients or on freelance platforms can help increase weekly income. Consistent remote work and advanced expertise are key to reaching this earning level.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Python, and cloud platforms remains critical for managing data workflows effectively.

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

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in Oklahoma? The most popular types of Data Engineering jobs in Oklahoma are:
What are popular job titles related to Remote Data Engineering jobs in Oklahoma? For Remote Data Engineering jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Oklahoma look for? The top searched job categories for Remote Data Engineering jobs in Oklahoma are:
What cities in Oklahoma are hiring for Remote Data Engineering jobs? Cities in Oklahoma with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Oklahoma as of July 2026, with employment types broken down into 73% Full Time, 6% Part Time, 5% Temporary, and 16% Contract. Highlights an 100% Remote job distribution, with an average salary of $119,772 per year, or $57.6 per hour.

Senior Data Engineer

SmartLight Analytics

Tulsa, OK • Remote

$96K - $131K/yr

Full-time

Re-posted 19 days ago

Job description

We are seeking a Senior Data Engineer with deep expertise in data warehousing, ETL pipeline development, and Snowflake to lead the modernization of our data infrastructure. In this role, you will build new data pipelines and warehouse models in Snowflake while partnering with our existing SQL Server Data Engineering team to migrate legacy systems to the cloud. You will work with healthcare claims, eligibility, and related data ingested from carrier and TPA partners, as well as data aggregated from internal systems.
This is a hands-on technical role requiring strong self-management, a proven ability to mentor peers, and comfort working with sensitive healthcare data under strict security requirements. As a scaling technology organization, we value ownership, collaboration, and continuous improvement — you will have a direct hand in shaping the tools, processes, and architecture that power our data platform.
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.Key Responsibilities
  • Design, build, and maintain ETL and reverse-ETL pipelines between Snowflake, Azure Data Factory, and legacy SQL Server systems.
  • Develop and optimize Snowflake data warehouse models, ensuring performance, reliability, and high availability.
  • Implement and maintain row-level and column-level security policies to protect sensitive healthcare data.
  • Partner with the existing SQL Server Data Engineering team to plan and execute the migration of legacy ETL processes and warehouse models to Snowflake and the cloud.
  • Build and maintain data transformations using dbt.
  • Monitor pipeline health, troubleshoot failures, and ensure uptime and data integrity across all data flows.
  • Mentor peers and contribute to engineering best practices, code reviews, and documentation.
  • Learn and adopt Sigma as the organization’s BI and reporting tool.
Required Skills and Qualifications
  • Bachelor’s degree in Computer Science, Data Engineering, or related field, or equivalent experience.
  • 10+ years of experience in data engineering, ETL development, and data warehouse modeling.
  • Proven hands-on experience with Snowflake, including architecture, optimization, and security.
  • Strong proficiency in SQL and Python.
  • Experience with at least one major BI/visualization platform (e.g., Power BI, Tableau, Looker, Sigma).
  • Experience with dbt and Azure Data Factory.
  • Prior experience working with healthcare data, including familiarity with data sensitivity, HIPAA, and security best practices.
  • Experience implementing row-level and/or column-level security in a data warehouse environment.
  • Strong self-management skills with the ability to work independently in a fully remote environment.
Preferred Qualifications
  • Experience with healthcare claims, eligibility, or related payer/TPA data.
  • Experience migrating data infrastructure from SQL Server to Snowflake or other cloud platforms.
  • Familiarity with Sigma.
  • Experience working in Agile development environments with tools such as Jira.
  • Prior experience in a startup or fast-growing technology company.
About SmartLight AnalyticsSmartLight Analytics was formed by a group of industry insiders who sought to reduce rising healthcare costs for self-funded employers. Through proprietary data analysis, SmartLight identifies and mitigates wasteful healthcare spending without disrupting employee benefits or requiring behavior changes.

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