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Databricks Data Engineer Jobs in Santa Clara, CA

iLink Digital

Databricks Engineer

Milpitas, CA · On-site

Databricks Engineer Experience 4-8 years Location As per business requirement Employment Type ... Integrate data from various sources including relational databases, APIs, cloud storage, and ...

Databricks

Principal Data Scientist

Mountain View, CA · On-site

Databricks is looking for a Principal Data Scientist to serve as the statistical voice of the Data ... Partner with engineering VPs, product leaders, and executive staff to embed a data-driven decision ...

Perficientcorp Inc

Data Engineer

Santa Clara, CA · On-site

$134K - $161K/yr

Proven hands-on expertise in data engineering with Snowflake and Databricks, including building and optimizing large-scale data pipelines. Strong understanding of data architecture fundamentals such ...

Glow Networks

Data Engineer

Mountain View, CA · On-site

$135K - $162K/yr

Job Role: Data Engineer Location: Mountain View, CA (Hybrid 3days onsite, 2 days remote ... Leverage advanced tools like Databricks for big data processing, ensuring the data is accessible ...

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Lead architecture and design of complex data pipelines on Databricks lakehouse architecture (Unity Catalog, Delta Lake, Structured Streaming) * Define technical approach for data engineering ...

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Lead architecture and design of complex data pipelines on Databricks lakehouse architecture (Unity Catalog, Delta Lake, Structured Streaming) * Define technical approach for data engineering ...

Blue Rose Technologies LLC

Fabric Data Engineer

Fremont, CA · On-site

$125K - $150K/yr

Azure Data Engineer Fremont, CA - Hybrid (Locals Only) 12 months Required Experience: 12+ years Key ... SQL, Python, Pyspark, Azure, Azure Databricks, Fabric, ADLS/ADF etc. * 10 + years of proven ...

New

Inficare Technologies

Snowflake Data Engineer

Santa Clara, CA · On-site

$134K - $161K/yr

Proven hands-on expertise in data engineering with Snowflake and Databricks , including building and optimizing large-scale data pipelines. * Strong understanding of data architecture fundamentals ...

BayRock Labs

Principal Data Engineer

Milpitas, CA · On-site

They are seeking a highly skilled Senior Data Engineer / Data Architect with extensive experience in Azure and Databricks to build large-scale data platforms and deliver high-quality data products in ...

Bayrock Labs

Principal Data Engineer

Milpitas, CA · On-site

$80 - $85/hr

As a leading product engineering firm based in Silicon Valley, we provide full-cycle product ... CI/CD for Databricks workloads Big Data & Processing Frameworks * Apache Spark with advanced ...

Rays Techsolutions Inc.

Senior Data Engineer

San Jose, CA · On-site

$124K - $168K/yr

Senior Data Engineer Location: San Jose, California, United States Experience: 8 10 Years Job ... Strong hands-on experience with Databricks , AWS , PySpark , Python , SQL , and Apache Airflow

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All JobsDatabricks Data Engineer JobsDatabricks Data Engineer Jobs in Santa Clara, CA

Databricks Data Engineer information

See Santa Clara, CA salary details

$52.3K

$152.3K

$208.5K

How much do databricks data engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for databricks data engineer in Santa Clara, CA is $152,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $161,500.00 per year, depending on experience, location, and employer.

What is a Databricks data engineer?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a Databricks data engineer do?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

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

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

How much does a Databricks data engineer make?

A Databricks Data Engineer typically earns between $90,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in Spark, cloud platforms, and data pipeline development can earn higher salaries.

Is a Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.

What are the most commonly searched types of Databricks Data Engineer jobs in Santa Clara, CA?

The most popular types of Databricks Data Engineer jobs in Santa Clara, CA are:

What are popular job titles related to Databricks Data Engineer jobs in Santa Clara, CA?

For Databricks Data Engineer jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Databricks Data Engineer jobs in Santa Clara, CA look for?

The top searched job categories for Databricks Data Engineer jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Databricks Data Engineer jobs?

Cities near Santa Clara, CA with the most Databricks Data Engineer job openings:

Databricks Data Engineer jobs near you
Infographic showing various Databricks Data Engineer job openings in Santa Clara, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $152,344 per year, or $73.2 per hour.

Databricks Engineer

iLink Digital

Milpitas, CA • On-site

Full-time

Re-posted 2 days ago

Job description


Role: Databricks Engineer
Experience
4-8 years
Location
As per business requirement
Employment Type
Full-time
Job Summary
We are looking for a skilled Databricks Engineer with strong expertise in designing, developing, and optimizing modern data engineering solutions on the Databricks Lakehouse Platform. The ideal candidate should have experience building scalable ETL/ELT pipelines, working with large-scale data, and leveraging Apache Spark to deliver high-performance data solutions.
Key Responsibilities
  • Design, develop, and maintain scalable data pipelines using Databricks.
  • Build ETL/ELT workflows for batch and streaming data processing.
  • Develop solutions using PySpark, Spark SQL, and Delta Lake.
  • Implement Medallion Architecture (Bronze, Silver, Gold) for data transformation.
  • Integrate data from various sources including relational databases, APIs, cloud storage, and streaming platforms.
  • Optimize Spark jobs for performance, scalability, and cost efficiency.
  • Collaborate with Data Architects, Data Scientists, BI developers, and business stakeholders.
  • Implement CI/CD pipelines and deployment automation for Databricks workloads.
  • Ensure data quality, security, governance, and compliance.
  • Monitor, troubleshoot, and optimize production data pipelines.
  • Document technical solutions and follow engineering best practices.
Required Skills
Core Technologies
  • Databricks Lakehouse Platform
  • Apache Spark
  • PySpark
  • Spark SQL
  • Delta Lake
  • Python
  • SQL
Cloud Platforms (one or more)
  • Microsoft Azure (preferred)
  • AWS
  • Google Cloud Platform
Azure Technologies (Preferred)
  • Azure Data Factory (ADF)
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure Synapse Analytics
  • Azure Key Vault
  • Azure DevOps
Data Engineering
  • Data Warehousing
  • Data Modeling
  • ETL/ELT Development
  • Batch Processing
  • Streaming (Kafka/Event Hubs)
  • Data Lake Architecture
DevOps & Version Control
  • Git
  • Azure DevOps / GitHub
  • CI/CD Pipelines
Preferred Qualifications
  • Experience with Unity Catalog.
  • Knowledge of Databricks Workflows and Jobs.
  • Hands-on experience with Delta Live Tables (DLT).
  • Exposure to MLflow is an added advantage.
  • Experience with data governance and security best practices.
  • Familiarity with Infrastructure as Code (Terraform) is a plus.
Educational Qualification
  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Preferred Certifications
  • Databricks Certified Data Engineer Associate
  • Databricks Certified Data Engineer Professional
  • Microsoft Certified: Azure Data Engineer Associate (DP-203)
  • Azure Fundamentals (AZ-900)
Good to Have
  • Experience with real-time analytics.
  • Knowledge of Lakehouse architecture.
  • Experience with Agile/Scrum methodologies.
  • Strong analytical and problem-solving skills.
  • Excellent communication and stakeholder management abilities.

Mandatory Skills
  • Databricks
  • PySpark
  • Spark SQL
  • Delta Lake
  • Python
  • SQL
  • Azure/AWS/GCP (at least one cloud platform)
  • ETL/ELT Development
  • Data Lake Architecture
Nice to Have
  • Unity Catalog
  • Delta Live Tables (DLT)
  • MLflow
  • Kafka/Event Hubs
  • Azure Data Factory
  • Terraform
  • Azure DevOps/GitHub Actions

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