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Associate Data Engineer Jobs in Fontana, CA (NOW HIRING)

Lobel Financial Corporation

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Sr. Data Engineer, Mircosoft Fabric

Anaheim, CA · On-site

$110K - $170K/yr

Fabric Data Engineer Associate or another relevant Microsoft certification. · Experience with Power BI, semantic models, Direct Lake, DAX, and enterprise reporting. · Experience with Delta Lake ...

Rkagroup

ASSOCIATE ENGINEER II (PE-2)

Walnut, CA · On-site

$94.86 - $115.94/hr

ASSOCIATE ENGINEER II (PE-2) Salary DOE - Starting at $105,401.83 Department Engineering Job Type ... Evaluate design alternatives and make sound, data-driven recommendations. * Interpret and apply ...

L3HHCM20

Associate, Software Engineer

Yorba Linda, CA

$75K - $140K/yr

Job Title: Associate, Software Engineering Job Code: 38768 Job Location: Yorba Linda, CA Job ... Utilize modeling tools and equipment to establish operating data, conduct experimental tests, and ...

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How much do associate data engineer jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for associate data engineer in Fontana, CA is $19.05, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $20.29 per hour, depending on experience, location, and employer.

What does an associate data engineer do?

An Associate Data Engineer is responsible for supporting the development, maintenance, and optimization of data pipelines and databases. They work closely with senior data engineers and other IT professionals to ensure data is accessible, reliable, and efficiently processed for analytics and business use. Typical tasks include writing and testing code for data integration, troubleshooting data issues, and implementing data security best practices. This entry-level position is a foundational role that builds technical skills and experience in data engineering.

What are the key skills and qualifications needed to thrive as an associate data engineer?

To thrive as an Associate Data Engineer, you need a solid understanding of data modeling, SQL, Python, and foundational knowledge of database concepts, often backed by a degree in computer science or a related field. Familiarity with data warehousing tools (like AWS Redshift, Google BigQuery), ETL frameworks, and cloud platforms as well as industry certifications such as AWS Certified Data Analytics is beneficial. Strong problem-solving skills, attention to detail, and effective communication help you navigate complex data challenges and collaborate with teams. These abilities are crucial for ensuring data systems are reliable, scalable, and aligned with organizational goals.

What are some common challenges an associate data engineer may face when working with large-scale data pipelines?

As an Associate Data Engineer, you may often encounter challenges such as optimizing data pipeline performance, ensuring data quality, and troubleshooting bottlenecks when processing large volumes of data. Working with distributed systems can introduce complex issues like latency and data consistency. Collaborating effectively with data scientists, analysts, and senior engineers is crucial for aligning data infrastructure with evolving project requirements. Regularly learning new tools and best practices will help you adapt to these challenges and grow in your role.

What is the difference between Associate Data Engineer vs Data Engineer?

AspectAssociate Data EngineerData Engineer
Required CredentialsBachelor's degree in CS, Data Science, or related field; basic knowledge of SQL and PythonBachelor's or Master's degree; advanced knowledge of SQL, Python, Spark, and cloud platforms
Work EnvironmentEntry-level, team-focused, often in tech or finance industriesMid to senior level, designing and maintaining data pipelines in various industries
Employer & Industry UsageCommon in tech companies, startups, and finance firmsUsed across industries for building scalable data infrastructure
Common Search & ComparisonOften compared for career progression and skill requirements

The Associate Data Engineer role is an entry-level position focusing on supporting data infrastructure, while the Data Engineer is a more advanced role responsible for designing and maintaining complex data systems. The roles share similar educational backgrounds and work environments but differ in experience level and responsibilities.

Is an associate data engineer entry level?

An associate data engineer is typically an entry-level position suitable for candidates with limited professional experience in data engineering. It often requires foundational skills in SQL, Python, or cloud platforms and serves as a starting point for a career in data engineering.

What are the most commonly searched types of Data Engineer jobs in Fontana, CA?

The most popular types of Data Engineer jobs in Fontana, CA are:

What are popular job titles related to Associate Data Engineer jobs in Fontana, CA?

For Associate Data Engineer jobs in Fontana, CA, the most frequently searched job titles are:

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The top searched job categories for Associate Data Engineer jobs in Fontana, CA are:

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Cities near Fontana, CA with the most Associate Data Engineer job openings:

Associate Data Engineer jobs near you
Infographic showing various Associate Data Engineer job openings in Fontana, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $39,623 per year, or $19 per hour.

Sr. Data Engineer, Mircosoft Fabric

Anaheim, CA • On-site

Lobel Financial Corporation
Finance and Insurance • 501 - 1,000 employees
Learn more about Lobel Financial Corporationexternal

$110K - $170K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Summary


We are seeking a Senior Data Engineer with hands-on Microsoft Fabric experience to design, build, migrate, and support enterprise data platforms. This role develops scalable ETL and ELT pipelines, implements Medallion Architecture in OneLake, Lakehouse, and Fabric Warehouse, and delivers reliable data for analytics and Power BI. The engineer partners with architects, application teams, analysts, BI developers, infrastructure teams, and business stakeholders to implement secure, governed, and high-performing data solutions.


Core Skills

· Microsoft Fabric architecture and engineering: Microsoft Fabric, Data Factory, Data Pipelines, Dataflows Gen2, OneLake, Lakehouse, Fabric Warehouse, Notebooks, and Medallion Architecture.

· Data pipeline development and programming: ETL/ELT, SQL, T-SQL, Python, PySpark, Spark, batch processing, incremental processing, change data capture (CDC), upsert/merge strategies, and metadata-driven frameworks.

· Data migration, warehousing, and modeling: legacy platform migration, source-to-target mapping, data profiling, cleansing, reconciliation, validation, dimensional modeling, star schemas, fact tables, dimension tables, and slowly changing dimensions.


Key Responsibilities

· Design, develop, test, deploy, and maintain scalable end-to-end data pipelines for batch, incremental, and near-real-time processing.

· Build data ingestion and transformation solutions using Microsoft Fabric Data Factory, Data Pipelines, Dataflows Gen2, Notebooks, SQL, Python, PySpark, Spark, and T-SQL.

· Develop reusable, metadata-driven ETL/ELT frameworks that support relational databases, APIs, files, SaaS applications, cloud platforms, and structured or semi-structured data.

· Implement CDC, incremental loads, upsert/merge patterns, historical processing, error handling, monitoring, and data-quality controls.

· Lead legacy-to-modern data migrations, including data profiling, source-to-target mapping, cleansing, transformation, reconciliation, validation, and cutover support.

· Design and implement Medallion Architecture using OneLake, Fabric Lakehouse, and Fabric Warehouse.

· Create enterprise data warehouse models using dimensional modeling, star schemas, fact tables, dimension tables, and slowly changing dimensions.

· Troubleshoot pipeline, data, integration, and performance issues and optimize Microsoft Fabric workloads and capacity utilization.

· Document data flows, mappings, standards, lineage, and operating procedures.

· Collaborate with technical and business stakeholders to deliver secure, governed, reliable, and scalable data solutions.


Required Qualifications

·5+ years of professional experience in data engineering, data integration, data warehousing, business intelligence, or a related field.

· Hands-on experience implementing Microsoft Fabric in a production or enterprise environment.

· Experience with Microsoft Fabric Data Factory, Data Pipelines, Dataflows Gen2, OneLake, Lakehouse, Fabric Warehouse, and Notebooks.

· Experience designing and implementing Medallion Architecture and enterprise ETL/ELT solutions.

· Strong SQL and T-SQL development skills.

· Strong Python and/or PySpark experience for data engineering and transformation.

· Experience with Spark-based batch and incremental data processing.

· Experience with legacy-to-modern data migration, data profiling, source-to-target mapping, transformation, reconciliation, and validation.

·Strong knowledge of data warehousing and dimensional modeling, including star schemas, fact tables, dimension tables, and slowly changing dimensions.

· Experience with data quality, monitoring, error handling, troubleshooting, and performance optimization.

· Strong analytical, problem-solving, written communication, verbal communication, and documentation skills.


Preferred Qualifications

· Microsoft Certified: Fabric Data Engineer Associate or another relevant Microsoft certification.

· Experience with Power BI, semantic models, Direct Lake, DAX, and enterprise reporting.

· Experience with Delta Lake, Snowflake, SQL Server, Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, or Azure Databricks.

· Experience integrating APIs and REST services and working with JSON, XML, or other semi-structured data.

· Experience with streaming or near-real-time data integration.

· Experience with enterprise data governance, metadata management, data lineage, cataloging, and automated data-quality testing.

· Experience supporting large-scale modernization or data migration programs.

· Experience working in Agile or Scrum environments.

· Experience mentoring data engineers and establishing engineering standards.

Company Description

Lobel Financial is a full-spectrum auto financing solution that specializes in the acquisition and servicing of prime to sub-prime motor vehicle retail installment contracts. We are head quartered in Southern California and have a market presence coast-to-coast.

Employees choose Lobel because of the work-life balance, positive company culture, reward system, benefits and flexibility. If you are an employee and you want to work with a company that is consistently growing, offers competitive salaries and benefits, promotes their employees, and provides a stable work environment, then you've found it with Lobel.

Lobel Financial is an equal opportunity employer.