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Contract Databricks Developer Jobs in California

Mondo

Senior Databricks Data Engineer

Marina Del Rey, CA · On-site

$200K - $225K/yr

Implement curated data products with clear contracts covering schemas, SLAs, data quality rules ... Experience with CI/CD for Databricks assets using Azure DevOps or GitHub Actions, and familiarity ...

New

Lorven Technologies

Software Developer

San Jose, CA · On-site

San Jose, CA - Onsite Contract role Tech Stack: Microsoft Azure, Microsoft Dynamics, Databricks, SnapLogic, Middleware Position Overview We are seeking a highly skilled Software Development Engineer ...

New

Compunnel

Senior DevOps Engineer

San Francisco, CA · On-site

$153K - $196K/yr

plaintext JOB SUMMARY Contract Sr. DevOps Engineer roles for one year assignments to implement and ... Implement and configure data engineering tools including Databricks, Immuta, Starburst, and ...

Saransh Inc

Lead Data Engineer - Only W2

San Francisco, CA · On-site

$134K - $162K/yr

W2 Contract Contract Length: 9 months with possible extension Experience Level: Senior/Lead Main ... SQL, Databricks, ADF, DataStage (or other ETL tool), SSAS cubes, Cognos/other, Tableau/other ...

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Contract Databricks Developer information

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 the most commonly searched types of Databricks Developer jobs in California? The most popular types of Databricks Developer jobs in California are:
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Contract Databricks Developer jobs near you

Senior Databricks Data Engineer

Mondo

Marina Del Rey, CA • On-site

$200K - $225K/yr

Contractor

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New

Job description

Job Title: Senior Databricks Data Engineer Location-Type: Onsite, Santa Monica, CA (office relocation to Century City anticipated within approximately one year) Start Date: ASAP Duration: Permanent Compensation Range: $200,000 - $225,000 Benefits: Medical premiums 100% covered, Dental and Vision premiums 100% covered, 401K with employer match up to 6%, 14 days PTO, 9 sick days annually, 11 paid holidays, $20K lifetime fertility benefit, daily catered lunch, weekly carwash service, monthly cellphone reimbursement Visa Sponsorship: Not eligible for visa sponsorship Job Description: This role leads the technical design and hands-on development of an enterprise-grade Azure Databricks Lakehouse platform, delivering scalable data infrastructure and governance capabilities across the organization. Job Summary •Build and evolve an internal Azure Databricks Lakehouse platform using Delta Lake and standardized architectural patterns such as medallion architecture. •Develop scalable ingestion and transformation frameworks for multiple source systems using Auto Loader, CDC incremental patterns, and Delta best practices. •Implement curated data products with clear contracts covering schemas, SLAs, data quality rules, ownership, and documentation. •Operationalize pipelines using Databricks Workflows, including scheduling, dependencies, retries, alerting, and run-time observability. •Own performance and cost optimization across workloads, including cluster policies, partitioning strategies, file sizing, and caching. •Implement and administer data governance and security using Unity Catalog, including least-privilege access patterns and audit standards. •Mentor junior and mid-level engineers, lead architecture and design reviews, and drive adoption of platform standards and best practices. Minimum Requirements: •8 years of data engineering experience, including 3 years of recent, hands-on Azure Databricks experience in production environments. •Strong proficiency in Python (PySpark) and Spark SQL for large-scale data transformation. •Strong experience with Delta Lake, including MERGE/UPSERT, schema evolution, time travel, ACID transactions, and incremental processing. •Solid Azure fundamentals relevant to a data platform, including ADLS Gen2, service principals, managed identities, and Azure Key Vault secrets management. •Demonstrated ability to work cross-functionally and communicate technical decisions clearly to non-engineering stakeholders. •Experience with financial datasets such as general ledger, subledger, and accounting line items. Preferred Qualifications: •Databricks Certified Data Engineer Professional certification (Associate certification also considered). •Experience implementing Unity Catalog in an enterprise environment, including RBAC model design and audit patterns. •Experience with CI/CD for Databricks assets using Azure DevOps or GitHub Actions, and familiarity with Terraform or asset-bundle deployment. •Experience with streaming or near-real-time ingestion using Structured Streaming, Event Hubs, or Delta Live Tables. •Private equity, credit, or alternative asset management industry experience. •Bachelor's degree in computer science, data engineering, mathematics, or a related field (preferred but not required).