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Contract Databricks Data Engineer Jobs in California

Data Engineer

Bay Point, CA · On-site

$125K - $151K/yr

Databricks Data Engineer Location: [Bay Area, CA] Duration : 12+ Months Need experience with Databricks Job Summary: We are seeking a skilled Data Engineer with hands-on Databricks experience to ...

Databricks Data Engineering Manager

Sacramento, CA · On-site

$122K - $146K/yr

Work you'll do As a Lead Data Engineer II in our AI & Data practice, you will leverage your ... Professional Databricks certifications (e.g., Data Engineer Professional, Machine Learning ...

Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution ... Experience with Databricks, including Delta Lake and Unity Catalog, is a plus. * Prior experience ...

Data Engineer

Rancho Cordova, CA · On-site

$122K - $146K/yr

Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution ... Experience with Databricks, including Delta Lake and Unity Catalog, is a plus. * Prior experience ...

Data Engineer

Pasadena, CA · On-site

$90K - $150K/yr

Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution ... Experience with Databricks, including Delta Lake and Unity Catalog, is a plus. * Prior experience ...

Data Engineer

Pasadena, CA · On-site

$124K - $150K/yr

Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution ... Experience with Databricks, including Delta Lake and Unity Catalog, is a plus. * Prior experience ...

Entry Level Data/AI Engineer

San Diego, CA · On-site

$121K - $146K/yr

... engineering, business intelligence, cloud data platforms, SQL development, AI-enabled data ... Databricks, Data Warehousing, Data Modeling, Applied AI/ML, Azure OpenAI, RAG, and LLM concepts.

Staff Data Engineer

San Diego, CA

$121K - $146K/yr

You will own a defined slice of our centralized Databricks data platform with full accountability for decisions and delivery, serve as a technical counterpart to the Principal Data Platform Engineer ...

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 ...

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Contract Databricks Data Engineer information

What are some common challenges faced by contract Databricks Data Engineers when integrating data from multiple sources?

As a contract Databricks Data Engineer, you'll often encounter challenges related to integrating diverse data sources, such as on-premises databases, cloud storage, and APIs. These challenges may include handling inconsistent data formats, managing data quality, and ensuring secure data transfers. Additionally, adapting to clients' unique data architectures and optimizing ETL pipelines for performance in a cloud environment are common tasks. Collaboration with data scientists, analysts, and other engineers is critical to ensure data is both accessible and reliable for downstream analytics and machine learning.

What are Contract Databricks Data Engineers?

Contract Databricks Data Engineers are professionals hired on a temporary or project basis to design, build, and maintain data infrastructure using Databricks, a unified analytics platform. They typically work with big data tools, cloud environments, and programming languages like Python or Scala to process and analyze large datasets. Their responsibilities often include developing data pipelines, optimizing data workflows, and collaborating with data scientists and analysts to support business objectives. Because they are contractors, their roles can vary by project and organization, offering flexibility and specialized expertise.

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

To excel as a Contract Databricks Data Engineer, you need strong experience in data engineering, SQL, Spark, and cloud platforms, often supported by a degree in computer science or a related field. Familiarity with Databricks, Apache Spark, Python or Scala, and cloud services like AWS or Azure is typically required, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you work effectively in dynamic, project-based environments. These competencies ensure the efficient design and implementation of scalable data solutions, driving business insights and project success.
What are the most commonly searched types of Databricks Data Engineer jobs in California? The most popular types of Databricks Data Engineer jobs in California are:
What are popular job titles related to Contract Databricks Data Engineer jobs in California? For Contract Databricks Data Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Contract Databricks Data Engineer jobs in California look for? The top searched job categories for Contract Databricks Data Engineer jobs in California are:
What cities in California are hiring for Contract Databricks Data Engineer jobs? Cities in California with the most Contract Databricks Data Engineer job openings:
Infographic showing various Contract Databricks Data Engineer job openings in California as of July 2026, with employment types broken down into 1% As Needed, 65% Full Time, 18% Part Time, 2% Temporary, and 14% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

AWS Databricks Data Engineer

Tror AI for everyone

Los Angeles, CA • On-site

$123K - $148K/yr

Contractor

Posted yesterday


Job description

Job Title: AWS Databricks Data Engineer

Job Location: Los Angeles CA (Hybrid)

Hire type: FTE / CTH

Note: Only Locals to California

 

Job Description –

We are seeking a highly skilled AWS Data Engineer with strong expertise in SQL, Python, PySpark, Data Warehousing, and Cloud-based ETL to join our data engineering team. The ideal candidate will design, implement, and optimize large-scale data pipelines, ensuring scalability, reliability, and high performance. This role requires close collaboration with cross-functional teams and business stakeholders to deliver modern, efficient data solutions.

Key Responsibilities

1. Data Pipeline Development

  • Build and maintain scalable ETL/ELT pipelines using Databricks on AWS.
  • Leverage PySpark/Spark and SQL to transform and process large, complex datasets.
  • Integrate data from multiple sources including S3, relational/non-relational databases, and AWS-native services.

2. Collaboration & Analysis

  • Partner with downstream teams to prepare data for dashboards, analytics, and BI tools.
  • Work closely with business stakeholders to understand requirements and deliver tailored, high‑quality data solutions.

3. Performance & Optimization

  • Optimize Databricks workloads for cost, performance, and efficient compute utilization.
  • Monitor and troubleshoot pipelines to ensure reliability, accuracy, and SLA adherence.
  • Apply query optimization, Spark tuning, and shuffle minimization best practices when handling tens of millions of rows.

4. Governance & Security

  • Implement and manage data governance, access control, and security policies using Unity Catalog.
  • Ensure compliance with organizational and regulatory data‑handling standards.

5. Deployment & DevOps

  • Use Databricks Asset Bundles for deployment of jobs, notebooks, and configuration across environments.
  • Maintain effective version control of Databricks artifacts using GitLab or similar tools.
  • Use CI/CD pipelines to support automated deployments and environment setups.

Technical Skills (Required)

  • Strong expertise in Databricks (Delta Lake, Unity Catalog, Lakehouse Architecture, Table Triggers, Workflows, Delta Live Pipelines, Databricks Runtime, etc.).
  • Proven ability to implement robust PySpark solutions.
  • Hands‑on experience with Databricks Workflows & orchestration.
  • Solid knowledge of Medallion Architecture (Bronze/Silver/Gold).
  • Significant experience designing or rebuilding batch‑heavy data pipelines.
  • Strong background in query optimization, performance tuning, and Spark shuffle optimization.
  • Ability to handle and process tens of millions of records efficiently.
  • Familiarity with Genie enablement concepts (understanding required; deep experience optional).
  • Experience with CI/CD, environment setup, and Git-based development workflows.
  • Solid understanding of AWS cloud, including:
  • IAM
  • Networking fundamentals
  • Storage integration (S3, Glue Catalog, etc.)

Preferred Experience

  • Experience with Databricks Runtime configurations and advanced features.
  • Knowledge of streaming frameworks such as Spark Structured Streaming.
  • Experience developing real-time or near real-time data solutions.
  • Exposure to GitLab pipelines or similar CI/CD systems.

Certifications (Optional)

  • Databricks Certified Data Engineer Associate / Professional
  • AWS Data Engineer or AWS Solutions Architect certification

Thanks & Regards

Akhil

akhil@tror.ai