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Data Engineer Jobs in Rancho Cordova, CA (NOW HIRING)

Data Strategy-Manager

Sacramento, CA ยท On-site

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Data Governance- Manager

Sacramento, CA ยท On-site

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Google Data Specialist

Sacramento, CA ยท On-site

$70K - $196K/yr

You Are A hands-on Specialist with foundational experience in Data Engineering, Analytics, or Machine Learning-now building deep expertise in Google Cloud Platform (GCP). You are eager to apply ...

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Data Platform Engineer

Sacramento, CA ยท On-site

$60 - $68/hr

Data Platform Engineer Duration: 12+ months Contract Location : Sacramento, CA - US (Remote) What candidates will do: Build Databricks pipelines and transformations Experience Level Required: 8 to 12 ...

Showing results 21-40

Data Engineer information

See Rancho Cordova, CA salary details

$47.5K

$138.4K

$189.4K

How much do data engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for data engineer in Rancho Cordova, CA is $138,377.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,100.00 and $146,700.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

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

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

What are popular job titles related to Data Engineer jobs in Rancho Cordova, CA?

For Data Engineer jobs in Rancho Cordova, CA, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Rancho Cordova, CA look for?

The top searched job categories for Data Engineer jobs in Rancho Cordova, CA are:

What cities near Rancho Cordova, CA are hiring for Data Engineer jobs?

Cities near Rancho Cordova, CA with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Rancho Cordova, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $138,377 per year, or $66.5 per hour.

Lead Data Engineer - Generative AI in Sacramento, CA

NetworkPedia LLC

Sacramento, CA โ€ข On-site

$124K - $149K/yr

Other

Posted 2 days ago

New


Job description

Lead Data Engineer - Gen AI

Location: West Sacramento, CA Hybrid (2 3 days onsite per week)
Employment Type: Contract
Duration: 12 36 months

About the Role

We are seeking a Lead Developer Data, Business Intelligence & Generative AI to provide hands-on technical leadership across enterprise data, BI, AI/ML, and Generative AI initiatives.

The ideal candidate will bridge data engineering, business intelligence, cloud platforms, and Generative AI, leading technical teams from requirements and architecture through development, deployment, and ongoing production support. This role requires someone who can remain hands-on while working closely with both technical teams and business stakeholders.

Key Responsibilities
  • Lead developers and analysts delivering enterprise BI, data warehouse, GenBI, GenAI, and AI/ML solutions.
  • Guide projects through requirements, architecture, design, development, testing, deployment, and continuous improvement.
  • Design and support enterprise data warehouse and analytics solutions using AWS, Snowflake, and related cloud technologies.
  • Develop production-grade dashboards, reports, APIs, dimensional data models, semantic layers, and analytics applications.
  • Design and optimize ETL/ELT pipelines using tools such as Airflow, dbt, Matillion, and similar platforms.
  • Work with cloud data platforms including Snowflake, Amazon Redshift, BigQuery, and Azure Synapse.
  • Develop advanced SQL, including complex joins, window functions, optimization, troubleshooting, and performance tuning.
  • Build dimensional and semantic data models using star and snowflake schemas.
  • Develop BI solutions using Power BI, Tableau, Looker, or comparable platforms.
  • Build Natural Language-to-SQL/Text-to-SQL capabilities for conversational business intelligence.
  • Use OpenAI APIs and other LLM platforms to develop GenAI-enabled analytics solutions.
  • Apply prompt engineering techniques to improve the quality, reliability, and usefulness of AI-generated business insights.
  • Develop testing and validation approaches for GenAI and Text-to-SQL solutions, including controls for hallucinations and inaccurate outputs.
  • Leverage technologies such as Snowflake Cortex and AWS Bedrock for GenAI and analytics use cases.
  • Support AI/ML initiatives involving predictive analytics, statistical modeling, and machine learning.
  • Contribute to agentic AI workflows, AI orchestration, and enterprise GenAI solutions.
  • Develop intuitive analytics interfaces using technologies such as Streamlit, Chainlit, React, and modern UI/UX practices.
  • Support Docker, Kubernetes, CI/CD, Terraform, and Ansible within data and AI environments.
  • Monitor, troubleshoot, optimize, and support production data, BI, AI/ML, and GenAI solutions.
  • Apply security, governance, compliance, cloud strategy, and FinOps principles to enterprise data and AI initiatives.
  • Prepare architecture diagrams, technical documentation, presentations, recommendations, and other project artifacts.
  • Collaborate with business stakeholders, developers, analysts, vendors, and technical support teams.
  • Mentor team members and provide knowledge transfer and technical guidance.
Mandatory Skills & Qualifications
  • 10+ years of experience in data engineering, BI engineering, and/or analytics.
  • 5+ years leading teams of at least three members on enterprise BI or large-scale data warehouse initiatives.
  • 5+ years of experience with AI/ML and/or Generative AI technologies.
  • Demonstrated experience delivering production-grade BI or data products.
  • 2+ years working with ETL/ELT, cloud data warehouses such as Snowflake/Amazon Redshift, and orchestration/transformation tools such as Airflow or dbt.
  • 2+ years of experience with OpenAI APIs or comparable LLM platforms, including Natural Language-to-SQL/Text-to-SQL solutions.
  • 2+ years of hands-on prompt engineering for analytics, BI, or business insight applications.
  • 2+ years of advanced SQL experience, including joins, window functions, optimization, and performance tuning.
  • 2+ years of experience with dimensional data modeling, star/snowflake schemas, and semantic layers.
  • 2+ years of experience with a major BI platform such as Power BI, Tableau, or Looker.
  • Strong experience leading technical teams and collaborating with business and technical stakeholders.
Preferred Skills
  • Snowflake Cortex and/or AWS Bedrock.
  • Agentic AI and AI orchestration.
  • TensorFlow, PyTorch, or scikit-learn.
  • BigQuery and Azure Synapse.
  • Docker and Kubernetes.
  • Terraform and Ansible.
  • Streamlit, Chainlit, React, or similar technologies.
  • AWS, Snowflake, Power BI, Tableau, or AI/ML certifications.
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field.
Work Location

This is a hybrid role in West Sacramento, California, requiring onsite work 2 3 business days per week. Candidates must be able to meet the onsite requirement.

Why Join Us
  • Work with modern Data, BI, Cloud, AI/ML, and Generative AI technologies.
  • Lead high-impact enterprise data and AI initiatives.
  • Collaborate with technical and business teams across complex projects.
  • Opportunity for long-term engagement and technical leadership.
About NetworkPedia

NetworkPedia is a certified women-owned technology and talent solutions company, providing IT infrastructure, cybersecurity, managed services, and specialized recruitment across North Americas and beyond. Our mission is to empower organizations with secure, scalable, and innovative technology while building inclusive teams that reflect the communities we serve. As a trusted partner, we deliver expertise across networking, cloud, IT service management, and security operations, along with staffing solutions for niche technology roles. We are committed to diversity, equity, and inclusion (DEI) in all our hiring practices and ensure that our opportunities are open to all qualified applicants, without discrimination on the basis of age, gender, race, ethnicity, religion, sexual orientation, or disability.

How to Apply

Apply directly via LinkedIn Easy Apply. All applications are routed to our central recruitment email: .