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Dataops Jobs in California (NOW HIRING)

Data Engineer

Los Angeles, CA

$123K - $148K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Data Engineer

San Diego, CA

$121K - $146K/yr

Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization). * Any experience leveraging universal data distribution architectures within DOD ...

... DataOps. Delivered as a SaaS solution, Acceldata is trusted by leading global organizations such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hershey ...

Data Engineer

San Diego, CA · On-site

$122K - $147K/yr

Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization). * Any experience leveraging universal data distribution architectures within DOD ...

Data Platform Engineer, Senior Staff

San Diego, CA · On-site

$112K - $152K/yr

... DataOps roles * Expert-level experience with AWS, including networking, IAM, security, and multi-account environments * Strong hands-on experience with Databricks Lakehouse Platform, including:

Data Engineer

San Diego, CA · On-site

$122K - $147K/yr

Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization). * Any experience leveraging universal data distribution architectures within DOD ...

Data Engineer

San Francisco, CA

$134K - $162K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

Staff Data Architect

Long Beach, CA · On-site

$67 - $86.25/hr

Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes) * Experience with real-time streaming ...

Data Engineer

Palo Alto, CA

$134K - $161K/yr

... DataOps concepts and operating in cross-functional teams that include data engineering personas. * The measures of success for this role include delivering data pipelines with trusted, quality data ...

... DataOps. Delivered as a SaaS solution, Acceldata is trusted by leading global organizations such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hershey ...

Staff Data Architect

Long Beach, CA · On-site

$69.50 - $89.50/hr

... s/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes) • Experience with real-time streaming architectures and event ...

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Showing results 1-20

Dataops information

See California salary details

$12

$22

$35

How much do dataops jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for dataops in California is $22.83, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $23.70 per hour, depending on experience, location, and employer.

What are DataOps?

DataOps, short for Data Operations, is a set of practices, processes, and technologies that combine data engineering, data integration, and DevOps methodologies to improve the quality and speed of data analytics. DataOps aims to streamline the flow of data from source to value, enabling organizations to deliver reliable, high-quality data to stakeholders more efficiently. This approach emphasizes collaboration, automation, and monitoring throughout the data lifecycle to reduce errors and shorten development cycles. The ultimate goal of DataOps is to create an agile data pipeline that adapts quickly to changing business needs.

What is the difference between Dataops vs Data Engineer?

AspectDataopsData Engineer
Primary FocusAutomating data workflows, deployment, and operational efficiencyBuilding and maintaining data pipelines, storage, and infrastructure
Skills & CertificationsDevOps tools, scripting, cloud platforms, CI/CD practicesSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentCollaborates with DevOps, data teams, and operationsWorks closely with data scientists, analysts, and infrastructure teams
Industry UsageUsed in organizations focusing on data deployment and automationUsed in data infrastructure development and data pipeline creation

While both Dataops and Data Engineers work with data infrastructure, Dataops emphasizes automation, deployment, and operational efficiency, whereas Data Engineers focus on building and maintaining data pipelines and storage systems. Understanding these differences helps organizations assign the right roles for their data needs.

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

To thrive as a DataOps Engineer, you need expertise in data engineering, automation, cloud platforms, and a solid understanding of CI/CD pipelines, typically backed by a degree in computer science or related fields. Familiarity with tools like Apache Airflow, Kubernetes, Docker, Jenkins, and cloud services such as AWS, GCP, or Azure is commonly required, along with knowledge of scripting languages like Python or Bash. Strong collaboration, problem-solving, and communication skills help DataOps professionals work effectively across data, development, and operations teams. These abilities ensure reliable, scalable, and efficient data infrastructure, enabling organizations to quickly deliver high-quality data solutions.

How does a DataOps professional typically collaborate with data engineers, analysts, and other IT teams?

DataOps professionals play a key role in bridging the gap between data engineering, analytics, and IT by facilitating efficient, automated workflows and ensuring data quality across the pipeline. They often work closely with data engineers to streamline data integration and deployment processes, while collaborating with analysts to support timely access to reliable data. Regular communication and cross-functional teamwork are essential, as DataOps is responsible for implementing best practices that help different teams deliver insights faster and with fewer errors. This collaborative environment also encourages continuous feedback and process improvement.
What cities in California are hiring for Dataops jobs? Cities in California with the most Dataops job openings:
Infographic showing various Dataops job openings in California as of June 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $47,480 per year, or $22.8 per hour.

$123K - $148K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 29 days ago


Job description

DLA Piper is, at its core, bold, exceptional, collaborative and supportive. Our people are the backbone, heart and soul of our firm. Wherever you are in your professional journey, DLA Piper is a place you can engage in meaningful work and grow your career. Let's see what we can achieve. Together.

Summary

The Data Engineer, Solutions & Data role designs, builds, and operates data pipelines and data integration processes that translate raw data into trusted, usable datasets for analytics, reporting, and downstream solutions. The role focuses on operationalizing pipelines with governance and service expectations (SLAs), improving data quality and reusability, and enabling secure access to integrated data in support of business initiatives. In current initiatives, data engineering includes consolidating data from multiple sources into a central SQL-based integration point and performing field mapping and transformations, so solution teams can consume data consistently.

Location

This position can sit in any of our U.S. offices and offers a hybrid work schedule.


Responsibilities

Data Pipeline Engineering & Integration

  • Build and operationalize data pipelines across heterogeneous environments, aligning to governance principles and service expectations (SLAs).

  • Build and maintain ingestion, transformation, and publication of pipelines (data engineering practice) to deliver analytics-ready data.

  • Consolidate data from multiple sources into a centralized integration point (e.g., a single SQL Server instance) and manage field mappings and transformations to support consistent downstream consumption.

Data Platform & Storage

  • Design and implement data pipelines using Azure data technologies (e.g., Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS) to ingest, process, and deliver data from sources such as APIs and other systems.

  • Build and maintain data warehousing capabilities (e.g., Azure Synapse Analytics) to support analytics and reporting workloads.

Data Quality, Reliability & Operations

  • Identify, troubleshoot, and resolve data issues including data quality, integrity, latency, and security concerns; apply monitoring and operational best practices to keep pipelines reliable and performant.

  • Contribute to data quality and governance practices, including profiling datasets, defining quality rules, and establishing monitoring/remediation approaches.

Collaboration & Delivery (Agile Pod Model)

  • Work cross-functionally with engineers, analysts, and stakeholders to understand requirements and deliver data solutions that support sprint-based delivery.

  • Support pod-level delivery by producing reusable data assets and integration components that can be leveraged across multiple initiatives.

Desired Skills

  • Proficiency in SQL and Python.

  • Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS).

  • Data warehousing experience (Azure Synapse Analytics) and strong fundamentals in data modeling, warehousing, and governance.

  • Scripting/automation skills (PowerShell and related tooling) for platform operations and troubleshooting.

  • Preferred experience includes familiarity with additional programming languages such as Java, Scala, or Go; experience integrating data from multiple enterprise source systems into a central SQL-based integration layer; and familiarity with DataOps concepts and operating in cross-functional teams that include data engineering personas.

  • The measures of success for this role include delivering data pipelines with trusted, quality data with agreed service levels, enabling faster onboarding of new data and more consistent analytics/AI consumption and creating reduced manual effort through reusable integrations and standardized transformations, improved data reliability and operational readiness.


Minimum Education

  • High School or GED


Preferred Education

  • Bachelor's Degree in Computer Science, Engineering, or related field.


Minimum Years of Experience

  • 3 years of experience in data engineering and/or data platform engineering (pipelines, integration, and operational support).


Essential Job Expectations

While the specific job requirements of a DLA Piper position may vary depending upon scope of the job and area of specialty, there are certain universal requirements that are expected of all DLA Piper employees, which include but are not limited to:

  • Effectively communicate, verbally and in writing, with clients, lawyers, business professionals, and third parties;

  • Produce deliverables, answer phone calls, and reply to correspondence in an efficient and responsive manner;

  • Provide timely, accurate, and quality work product;

  • Successfully meet deadlines, expectations, and perform work duties as required;

  • Foster positive work relationships;

  • Comply with all firm policies and practices;

  • Engage in both physical and sedentary activity, such as (a) working at a computer for extended periods of time, including on-screen reading and typing; (b) participating in digital/virtual conference calls; (c) participating in meetings as needed;

  • Ability to work under pressure and manage competing demands in a fast-paced environment;

  • Perform all other duties, tasks or projects as assigned.

Our employees are expected to embrace and uphold our firm values as a part of our DLA Piper culture. We are committed to excellence in how we represent our clients and develop our people.

Physical Demands

Sedentary work: Exerting up to 10 pounds of force occasionally and/or a negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Sedentary work involves sitting most of the time. Jobs are sedentary if walking and standing are required only occasionally and all other sedentary criteria are met.


Work Environment

The individual selected for this position may have the opportunity for a hybrid work arrangement comprised of remote and in-office work, the requirement for which will be determined in coordination with the hiring manager or supervisor and may be modified in the firm's discretion in the future.
Disclaimer

The purpose of this job description is to provide a concise statement of the work elements and to organize and present the information in a standardized way. It is not intended to describe all the elements of the work that may be performed by every individual in this classification, nor should it serve as the sole criteria for personnel decisions and actions. The job duties, requirements, and expectations for this position may be modified at the Firm's discretion at any time. This job description does not change the at-will nature of employment.

Application Process

Applicants must apply directly online instead of sending application materials via email.

Accommodation

Reasonable accommodations may be made upon request to permit individuals with a disability to perform the essential functions and responsibilities of the position or to participate in the job selection process. If you have a request for an accommodation during the application process, please contact careers@us.dlapiper.com.

Agency applications will not be considered.

No immigration sponsorship is available for this position.


The firm's expected hiring range for this position is $100,787 - $160,255 depending on the candidate's geographic market location.

The compensation offered for employment will also be dependent on other factors including the candidate's experience, skills, educational and professional background, and overall qualifications. We offer a comprehensive package of benefits including medical/dental/vision insurance, and 401(k).

Applicants who are not based in the jurisdiction in which this position is posted and who apply for this role are doing so voluntary and are not eligible for relocation assistance. Any relocation benefits, if any, are provided only where a relocation is required at the firm's direction and in accordance with applicable policy and law.

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DLA Piper is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Job applicant poster viewing center.