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Contract Databricks Developer Jobs in California

SDH Systems

Lead Databricks Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Data Engineer Location- San Jose, CA- Onsite Contract role Requirements We are seeking a Lead Data Engineer with expertise in Databricks and Data Warehousing to drive data architecture, pipeline ...

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 ...

YO AI Labs

Senior Data Engineer

Glendale, CA

$112K - $152K/yr

Contract, On-site Must Haves: * Candidates must be willing to work on W2, no C2C. * 5+ years of data engineering experience specifically developing large-scale data pipelines. * Databricks and Python ...

New

Mondo

$130/hr

Contract Compensation Range: $130-150K Benefits: Eligible for Health, Dental, Vision, 401K, PTO ... Lead development and optimization of data pipelines using Databricks, SQL, Python, and PySpark

Mindsource Inc

AI Developer

Sacramento, CA · On-site

Sacramento, CA (Hybrid) Duration: 6-month Contract-to-Hire (C2H) Position Summary: We are seeking a ... Enterprise data platforms (Databricks, etc.) * Partner with business stakeholders to identify and ...

iFlow Inc

Senior Data Engineer

Palo Alto, CA · On-site

$124K - $169K/yr

Title: Senior Data Engineer Location: Palo Alto, CA Working Hours: 8am-5pm Duration:4 Months ... contract compliance across key pipelines. Optimize Databricks jobs, Fivetran connectors, and dbt ...

New

aKube, Inc.

Senior Data Engineer - 1628

Calabasas, CA · On-site

$130K - $150K/yr

Up to $130k to $150k PA depending on experience (no C2C or 1099 or sub-contract) Work Authorization: GC, USC Only Must Have: Databricks AI Python Azure API development ETL pipelines DevOps and CI/CD ...

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:
What are popular job titles related to Contract Databricks Developer jobs in California? For Contract Databricks Developer jobs in California, the most frequently searched job titles are:
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Contract Databricks Developer jobs near you
Lead Databricks Engineer

Lead Databricks Engineer

SDH Systems

San Jose, CA • On-site

$120K - $158K/yr

Other

Posted 17 days ago

Job description

Lead Data Engineer

Location- San Jose, CA- Onsite  

Contract role  

 Requirements

 We are seeking a Lead Data Engineer with expertise in Databricks and Data Warehousing to drive data architecture, pipeline development, and optimization efforts. The ideal candidate will play a key role in designing scalable solutions, implementing best practices, and leading data initiatives within a dynamic and collaborative environment.

Key Responsibilities:

  • Design, build, and optimize scalable data pipelines using Databricks, Apache Spark, and Azure technologies.
  • Architect data warehousing solutions, ensuring seamless integration with cloud platforms and structured/unstructured data sources.
  • Collaborate with business stakeholders to understand data needs and develop high-performance analytical solutions.
  • Implement ETL/ELT processes leveraging cloud-based technologies such as Azure Data Factory, Snowflake, and Delta Lake.
  • Ensure data quality, governance, and security compliance while managing large datasets efficiently.
  • Drive performance tuning and optimization for data pipelines, ensuring efficiency across systems.
  • Work closely with cross-functional teams to support machine learning and advanced analytics initiatives.
  • Provide technical leadership and mentorship to junior data engineers, fostering a culture of innovation and continuous improvement.
  • Stay updated on emerging data technologies and recommend strategies to enhance existing architectures.

Qualifications:

  • 8+ years of experience in data engineering, big data processing, and cloud-based solutions.
  • Strong expertise in Databricks, Spark (PySpark/SQL), and Delta Lake architecture.
  • Proven experience in designing and managing data warehouses using Snowflake, Azure Synapse, or equivalent technologies.
  • Deep understanding of data modeling, SQL, and performance optimization.
  • Hands-on experience with Azure Data Factory, Event Hubs, and cloud-based ETL processes.
  • Solid knowledge of real-time streaming technologies (Kafka, Azure Stream Analytics, or similar).
  • Familiarity with ML/AI data pipelines and feature engineering best practices.
  • Strong communication and collaboration skills, with experience working in fast-paced, enterprise environments.

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