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Freelance Databricks Data Engineer Jobs in Oklahoma

Pwc

Data Strategy & Governance -Director

Tulsa, OK · On-site

$155K - $410K/yr

... Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating thought leadership in data governance - Collaborating on strategy and transformation ...

Pwc

Data Strategy & Governance -Director

Oklahoma City, OK · On-site

$155K - $410K/yr

... Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating thought leadership in data governance - Collaborating on strategy and transformation ...

Worky

Senior AI Solutions Engineer

Oklahoma City, OK · On-site

$150 - $200/hr

Experience with enterprise AI technologies including Open WebUI, LiteLLM, n8n, Databricks, Glean, or comparable platforms. * Strong understanding of data engineering, data integration, and working ...

Pwc

AI & GenAI Data Scientist - Manager

Tulsa, OK · On-site

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Pwc

AI Engineer

Tulsa, OK · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Expand Energy

Sr. ML Ops Engineer

Oklahoma City, OK · On-site

$85K - $117K/yr

Hands-on experience with cloud-based data platforms and architectures, including Snowflake and Databricks * Strong knowledge of CI/CD, DevOps, and release management practices used to deploy and ...

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Freelance Databricks Data Engineer information

What is a freelance Databricks data engineer?

Freelance Databricks Data Engineers are independent professionals who specialize in designing, building, and maintaining data pipelines and analytics solutions using the Databricks platform. They work on a contract basis, often helping organizations with data integration, ETL processes, and leveraging Apache Spark for big data analytics. These engineers typically have expertise in cloud platforms, SQL, Python, and other data engineering tools, and they offer flexible support based on project needs.

What are the key skills and qualifications needed to thrive as a freelance Databricks data engineer?

To thrive as a Freelance Databricks Data Engineer, you need strong skills in data engineering, SQL, Python or Scala, and a solid understanding of big data concepts, often supported by a degree in computer science or related fields. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications (like Databricks Certified Data Engineer) is highly valued. Excellent problem-solving, communication, and self-management skills are essential for collaborating remotely with clients and handling diverse projects. These skills enable efficient data pipeline development, scalable analytics, and successful client delivery in dynamic freelance environments.

How do freelance Databricks data engineers typically collaborate with client teams during projects?

Freelance Databricks Data Engineers often work remotely and interact with client teams through regular virtual meetings, project management platforms, and collaboration tools like Slack or Microsoft Teams. Clear communication is crucial, as you'll coordinate closely with data scientists, analysts, and IT stakeholders to understand requirements, deliver solutions, and troubleshoot issues. Establishing a structured workflow and providing frequent progress updates help ensure alignment and project success. Flexibility and proactive problem-solving are especially important in adapting to each client's unique data infrastructure and business goals.

What is the difference between Freelance Databricks Data Engineer vs Freelance Data Engineer?

AspectFreelance Databricks Data Engineer

Required SkillsProficiency in Databricks, Spark, Python, SQL, cloud platforms
Work EnvironmentRemote, project-based, client-specific
CertificationsDatabricks certifications, cloud platform credentials
Industry UsageData analytics, big data projects, AI/ML integrations

Freelance Databricks Data Engineers specialize in building and maintaining data pipelines using Databricks and Spark, often working on big data projects in cloud environments. Freelance Data Engineers may have broader skills across various tools and platforms but might not focus specifically on Databricks. Both roles are remote, project-based, and require similar certifications, but the Databricks-specific expertise makes the Freelance Databricks Data Engineer more specialized in Databricks ecosystems.

What are the most commonly searched types of Databricks Data Engineer jobs in Oklahoma?

The most popular types of Databricks Data Engineer jobs in Oklahoma are:

What are popular job titles related to Freelance Databricks Data Engineer jobs in Oklahoma?

For Freelance Databricks Data Engineer jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Freelance Databricks Data Engineer jobs in Oklahoma look for?

The top searched job categories for Freelance Databricks Data Engineer jobs in Oklahoma are:

What cities in Oklahoma are hiring for Freelance Databricks Data Engineer jobs?

Cities in Oklahoma with the most Freelance Databricks Data Engineer job openings:

Freelance Databricks Data Engineer jobs near you

Senior Engineer - Data Science

Continental Resources, Inc.

Oklahoma City, OK • On-site

Full-time

Re-posted 21 days ago

Job description

Job Summary
The Senior Engineer, Data Science is a hands-on technical role who designs, builds, and operationalizes advanced analytics and Artificial Intelligence/Machine Learning solutions that drive measurable value across subsurface, drilling and completions, production operations, HSE, and commercial functions at Continental Resources. This role partners with multidisciplinary stakeholders to translate business problems into data-driven solutions, develop robust models and pipelines, and deploy them to production with strong Machine Learning Ops and governance practices. The ideal candidate combines a Master of Science in Data Science with strong applied analytics capability, solid data engineering skills, and practical oil and gas domain experience comparable to a seasoned upstream engineering background.
Duties and Responsibilities
  • Leads the design, development, and deployment of Artificial Intelligence/Machine Learning solutions for upstream subsurface and well operations, including physics-informed and hybrid modeling approaches for reservoir, drilling, and production optimization.
  • Builds advanced Artificial Intelligence/Machine Learning solutions for commercial analytics use cases such as pricing, supply chain, marketing, and trading to improve profitability and decision speed.
  • Executes complex AI initiatives from ideation and discovery through model development, deployment, and sustainment as part of integrated, enterprise-level teams.
  • Architects and implements reliable data pipelines and features using modern data platforms (e.g., Databricks, cloud services), ensuring data quality, lineage, and performance for analytics workloads.
  • Applies Machine Learning Ops best practices to automate training, testing, deployment, monitoring, and model lifecycle management at scale in production environments.
  • Translates complex business problems into analytical approaches with clear hypotheses, success criteria, and measurable outcomes across upstream and commercial domains.
  • Develops and delivers communications that convey a clear understanding of technical concepts, model results, and business implications to diverse technical and non-technical audiences.
  • Builds strong partnerships and cross-functional relationships with geoscience, engineering, operations, commercial, IT, and leadership stakeholders to drive adoption and sustain business impact.
  • Gains the confidence and trust of others through honesty, integrity, and follow-through while championing responsible and secure use of data and AI.
  • Actively seeks new ways to grow and be challenged by staying current on emerging Artificial Intelligence/Machine Learning, generative AI, optimization, and computational techniques relevant to energy and integrating them where they add value.
  • Other duties as assigned.

Skills and Competencies
  • Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
  • Action oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
  • Drives results - Consistently achieving results, even under tough circumstances.
  • Self-development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
  • Nimble learning - Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.
  • Situational adaptability - Adapting approach and demeanor in real time to match the shifting demands of different situations.
  • Instills trust - Gaining the confidence and trust of others through honesty, integrity, and authenticity.

Required Qualifications
  • Bachelor of Science in Petroleum, Mechanical, Chemical, or related Engineering discipline from an accredited college or university and Master of Science in Data Science, or a closely related data science or analytics field, from an accredited college or university.
  • Minimum five (5) years of hands-on experience delivering production-grade data science/Machine Learning solutions, including end-to-end lifecycle from discovery to deployment and sustainment.
  • Proficiency in Python and SQL; experience with Machine Learning frameworks and tooling (e.g., scikit-learn, PyTorch/TensorFlow), and data platforms such as Databricks and cloud services.
  • Experience building and maintaining data pipelines and features and applying Machine Learning Ops practices for model deployment and monitoring in enterprise environments.
  • Demonstrated ability to partner with technical and business domains in energy, including upstream subsurface, drilling/completions, production operations, and/or commercial analytics such as pricing, supply chain, marketing, or trading.
  • An acceptable pre-employment background and drug test.

Preferred Qualifications
  • Oil and gas industry experience, particularly in upstream engineering, subsurface, drilling and completions, production operations, or commercial energy analytics.
  • Background in computational sciences, optimization, or high-performance computing for engineering applications.
  • Familiarity with enterprise data governance, security, and responsible AI practices in regulated environments.
  • Five (5) or more years of combined oil and gas engineering/domain experience and applied data science experience.

Physical Requirements and Working Conditions
  • Requires prolonged sitting, some bending and stooping.
  • Occasional lifting up to 25 pounds.
  • Manual dexterity sufficient to operate a computer keyboard and calculator.

Continental Resources, Inc. provides equal employment opportunities and access for all applicants and employees without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, national origin, age, disability, genetic information, veteran status, or any other category protected by law.

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