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Contract Databricks Developer Jobs in Washington, DC

eTeam

Databricks Platform Engineer

Washington, DC · Remote

Contract Duration: 8 Months Location: Remote Role Summary: We are seeking a Databricks Platform Engineer to implement and operationalize core platform capabilities on Databricks running on AWS. This ...

ICF

Data Engineer (Databricks) - Remote USA

Reston, VA · Remote

$119K - $143K/yr

Citizenship required due to federal contract requirements. * Ability to obtain and maintain a ... and DevOps practices using Terraform for IaC. * Emergency management domain knowledge a plus

ICF

Technical Team Lead (AWS & Databricks)

Reston, VA · On-site

Lead a cross-functional Agile team (pod) of engineers, analysts, and testers to deliver data and ... S. Citizenship required due to federal contract requirements * Ability to obtain and maintain a ...

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All JobsContract Databricks Developer JobsContract Databricks Developer Jobs in Washington, DC

Contract Databricks Developer information

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$23

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$90

How much do contract databricks developer jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for contract databricks developer in Washington, DC is $69.64, according to ZipRecruiter salary data. Most workers in this role earn between $62.60 and $77.07 per hour, depending on experience, location, and employer.

What is a Contract Databricks Developer?

A Contract Databricks Developer is a data engineering professional hired on a temporary or project basis to develop, optimize, and maintain data pipelines and analytics solutions using the Databricks platform. They work with cloud data technologies, Spark, and big data frameworks to support organizations in managing large-scale data processing and analytics tasks. Their responsibilities often include building ETL workflows, collaborating with data scientists, and ensuring data quality and performance in data-driven projects.

What are some common challenges faced by Contract Databricks Developers when starting a new project?

As a Contract Databricks Developer joining a new project, you may encounter challenges such as quickly understanding the existing data architecture, adapting to the client's specific workflow, and ensuring seamless integration with their cloud infrastructure (often Azure or AWS). You’ll also need to align with established data governance and security protocols while collaborating with data engineers, analysts, and business stakeholders. Effective communication and proactive documentation are key to overcoming these hurdles and delivering value efficiently within the contract period.

What is the difference between Contract Databricks Developer vs Data Engineer?

AspectContract Databricks DeveloperData Engineer
Primary FocusDeveloping and optimizing data pipelines using Databricks platformDesigning, building, and maintaining scalable data architectures
Skills & CertificationsProficiency in Spark, SQL, Python, Databricks platform, and cloud servicesKnowledge of ETL processes, SQL, Python, cloud platforms, and data modeling
Work EnvironmentProject-based, often remote, with a focus on Databricks environmentsVaries from in-house teams to consulting, working on large-scale data systems

While both roles require expertise in data processing and cloud platforms, a Contract Databricks Developer specializes in building data solutions specifically within the Databricks environment, whereas a Data Engineer has a broader scope in designing and managing overall data infrastructure across various tools and platforms.

What are the key skills and qualifications needed to thrive as a Contract Databricks Developer, and why are they important?

To excel as a Contract Databricks Developer, you need strong expertise in data engineering, big data analytics, and proficiency in programming languages like Python or Scala, typically backed by relevant experience or a degree in computer science. Familiarity with Databricks, Apache Spark, cloud platforms (such as Azure or AWS), and certifications like Databricks Certified Associate Developer are commonly required. Excellent problem-solving, adaptability, and communication skills help you collaborate with clients and teams to deliver tailored data solutions. These competencies are crucial for building scalable data pipelines and efficiently managing large datasets in dynamic project environments.
What are popular job titles related to Contract Databricks Developer jobs in Washington, DC? For Contract Databricks Developer jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Contract Databricks Developer jobs in Washington, DC look for? The top searched job categories for Contract Databricks Developer jobs in Washington, DC are:
Contract Databricks Developer jobs near you
Databricks Platform Engineer

Databricks Platform Engineer

eTeam

Washington, DC • Remote

Other

Posted 12 days ago

Job description

Job Title: Databricks Platform Engineer
Job Type: Contract
Duration: 8 Months
Location: Remote
Role Summary:
We are seeking a Databricks Platform Engineer to implement and operationalize core platform capabilities on Databricks running on AWS. This role focuses on frameworks, automation, observability, and reliable delivery aligned to established platform standards.
Key Responsibilities:
Platform Engineering:
  • Implement metadata-driven ingestion frameworks and standard ingestion patterns
  • Build batch, incremental, and CDC ingestion pipelines
  • Ensure pipelines follow platform standards for configuration, schema evolution, tagging, and error handling
Observability & Operations:
  • Implement pipeline monitoring, metrics, and alerting
  • Support operational validation, failure simulation, and recovery testing
Data Quality & Governance:
  • Embed data quality rules and quarantine patterns
  • Apply Unity Catalog tags (domain, owner, sensitivity, freshness) at ingestion time
  • Ensure governance metadata is written to governed schemas
CI/CD & Automation:
  • Build CI/CD pipelines using GitHub Actions
  • Support configuration validation, environment promotion, and rollback
  • Ensure secret management via AWS Secrets Manager
Required Qualifications:
  • 5-8 years data or platform engineering experience
  • 3+ years hands-on Databricks experience
  • Strong PySpark and SQL
  • Experience with Delta Lake, Unity Catalog, Git-based development
Preferred Qualifications:
  • Ingestion framework experience
  • Monitoring and alerting implementation
  • Production platform support experience
Success Measures:
  • Stable, reusable ingestion frameworks
  • Reduced custom pipeline development
  • Reliable CI/CD and proactive operational monitoring

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