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Azure Data Factory Jobs in California (NOW HIRING)

Develop and manage data pipelines using Azure Data Factory (ADF) * Build and optimize data warehouse and data mart structures (raw → curated layers) * Perform data ingestion, transformation, and ...

Azure

San Francisco, CA · On-site

$64.75 - $80.50/hr

... Azure Data Factory, PowerBI, b) Microsoft SQL Server Ecosystem - Multidimensional cubes, MDX, T-SQL c) Hadoop Ecosystem - HDFS, Spark, MapReduce, Pig, Hive 2. Experience building Data warehouses ...

Data Engineer

Palo Alto, CA · On-site

$134K - $161K/yr

Lead the design and implementation of data pipelines and ETL processes using Azure Data Factory, Synapse, and other Azure services. * Architect and optimize data models and storage solutions for ...

Data Platform Engineer

La Mirada, CA · On-site

$115K - $138K/yr

Implement and support Azure data services, including Azure SQL Database, Azure SQL Managed Instance, Azure Data Factory, Azure Storage, Azure Key Vault, and related services. * Support Microsoft ...

Data Engineer

San Mateo, CA

$130K - $156K/yr

Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage (ADLS), and Azure SQL Deploy and manage cloud-based data infrastructure; leverage Azure DevOps for CI/CD of data ...

Senior Data Engineer

Pomona, CA · On-site

$114K - $140K/yr

Leads conversion of SSIS packages to Azure Data Factory, Snowflake OpenFlow and modern ELT frameworks * Designs scalable ingestion patterns to prevent duplicate extracts and enable incremental ...

Senior Data Engineer

Pomona, CA · On-site

$114K - $140K/yr

Leads conversion of SSIS packages to Azure Data Factory, Snowflake OpenFlow and modern ELT frameworks * Designs scalable ingestion patterns to prevent duplicate extracts and enable incremental ...

Azure With ADL/ADW/ADF

San Francisco, CA

$64.75 - $80.50/hr

Microsoft Cortana Analytics Suite - Azure Data Lake, Azure Datawarehouse, Azure Data Factory, PowerBI, * Microsoft SQL Server Ecosystem - Multidimensional cubes, MDX, T-SQL * Hadoop Ecosystem - HDFS ...

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Azure Data Factory information

See California salary details

$10

$57

$78

How much do azure data factory jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for azure data factory in California is $57.64, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $64.76 per hour, depending on experience, location, and employer.

What is an Azure Data Factory job?

An Azure Data Factory job refers to a data processing task executed within Azure Data Factory (ADF), a cloud-based data integration service. ADF enables the creation, scheduling, and orchestration of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) workflows. These jobs help in moving and transforming data between various data stores, such as Azure Blob Storage, SQL databases, and on-premises systems. By using pipelines, activities, and triggers, ADF automates data workflows efficiently.

Is ADF better than SSIS?

Azure Data Factory (ADF) and SQL Server Integration Services (SSIS) are both data integration tools, but ADF is a cloud-based service optimized for large-scale, cloud-native data workflows, while SSIS is an on-premises tool suited for traditional ETL processes. For jobs involving cloud data movement, ADF offers better scalability and integration with Azure services, whereas SSIS is preferred for on-premises environments and complex transformations requiring local resources.

Is Azure Data Factory in demand?

Azure Data Factory is a widely used cloud-based data integration service, and professionals with skills in this tool are in high demand due to the increasing adoption of cloud data solutions. Knowledge of data pipelines, ETL processes, and related Azure services enhances job prospects in data engineering and analytics roles.

What are the key skills and qualifications needed to thrive in the Azure Data Factory position, and why are they important?

To thrive in an Azure Data Factory role, you need expertise in data integration, ETL processes, and cloud data solutions, typically supported by a background in computer science or information technology. Familiarity with Microsoft Azure Data Factory, Azure SQL Database, and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly valued. Strong analytical thinking, effective communication, and problem-solving skills help professionals excel in cross-functional teams. These skills are essential for designing, deploying, and maintaining efficient data workflows that support business analytics and decision-making.

Is ADF difficult to learn?

Azure Data Factory (ADF) is a data integration service that requires understanding of data workflows, pipelines, and cloud-based tools. While it has a learning curve for beginners, familiarity with SQL, data transformation concepts, and cloud environments can help accelerate the learning process. Many users find that hands-on practice and official documentation make mastering ADF achievable within a reasonable timeframe.

What are some typical challenges faced by professionals working with Azure Data Factory, and how can they be addressed?

One of the main challenges in an Azure Data Factory role is managing complex data pipelines that span multiple data sources and destinations, which requires careful orchestration and monitoring. Troubleshooting data integration issues and ensuring data accuracy can also be demanding, especially when dealing with large volumes of data or evolving business requirements. Successful professionals often address these challenges by staying updated with Azure’s latest features, implementing robust error-handling, and collaborating closely with data architects and business analysts. Joining a supportive team environment and accessing ongoing training can further assist in overcoming common hurdles and advancing in your career.

What can you do with Azure Data Factory?

Azure Data Factory is a cloud-based data integration service that allows data engineers and analysts to create, schedule, and manage data pipelines for moving and transforming data across various sources and destinations. It supports data ingestion, data transformation using mapping and data flow activities, and orchestration of complex workflows, enabling efficient data processing and analytics. Knowledge of data integration, ETL processes, and familiarity with Azure environment are important for working with Azure Data Factory.
What are the most commonly searched types of Azure Data Factory jobs in California? The most popular types of Azure Data Factory jobs in California are:
What are popular job titles related to Azure Data Factory jobs in California? For Azure Data Factory jobs in California, the most frequently searched job titles are:
What job categories do people searching Azure Data Factory jobs in California look for? The top searched job categories for Azure Data Factory jobs in California are:
What cities in California are hiring for Azure Data Factory jobs? Cities in California with the most Azure Data Factory job openings:
Infographic showing various Azure Data Factory job openings in California as of June 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $119,886 per year, or $57.6 per hour.
Azure Data Engineer

$117K - $140K/yr

Full-time

Posted 14 days ago


Job description

Job Title: (Azure Data Engineer) with Lakehouse Platform
Location: Downey, CA, 90242 :: Remote
Duration: 12 Months
Skills Required
Possess knowledge and technical expertise in standards and technologies to support complex business analysis, solution selection, systems design, and application integration - SQL and Relational Databases such as Oracle, SQL Server - Designing & developing SQL queries, stored procedures, views, debugging & tuning complex queries for optimal performance - UNIX shell scripts - Python - Azure Cloud - Azure Data Factory - Databricks - DataOps.
This classification must have a minimum of
seven (7) years of applying Enterprise Architecture principles.
At least five (5) years of that experience must be in a lead capacity. Q
5 years of experience in Azure Data Factory
5 years of experience in Databricks
5 years of experience in Managing Azure Resources
5 years of experience in automating Azure Data Resources using DataOps
5 years of experience in developing data models and data pipelines using Python
5 years of experience in Lakehouse Platform.
Education:
This classification requires the possession of a bachelor's degree in an IT-related or Engineering field. Additional qualifying experience may be substituted for the required education on a year-for-year basis.