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Dataops Engineer Jobs in Texas (NOW HIRING)

Data Engineer

Houston, TX

$109K - $131K/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

Austin, TX

$113K - $136K/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 ...

Follow software engineering and DataOps practices to develop automation solutions for manual data validation, reconciliation, and incident response processes. * Champion implementation of innovative ...

Follow software engineering and DataOps practices to develop automation solutions for manual data validation, reconciliation, and incident response processes. * Champion implementation of innovative ...

Follow software engineering and DataOps practices to develop automation solutions for manual data validation, reconciliation, and incident response processes. * Champion implementation of innovative ...

Senior Data Engineer

Austin, TX

$105K - $142K/yr

Implement DataOps practices with automated testing and deployment pipelines (CI/CD for data) Data Engineering & Analysis * Develop and maintain Python-based data processing frameworks and utilities

Senior Data Engineer

Austin, TX

$105K - $142K/yr

Implement DataOps practices with automated testing and deployment pipelines (CI/CD for data) Data Engineering & Analysis * Develop and maintain Python-based data processing frameworks and utilities

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Dataops Engineer information

See Texas salary details

$20

$55

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How much do dataops engineer jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for dataops engineer in Texas is $55.85, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $61.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Dataops Engineer position, and why are they important?

To thrive as a Dataops Engineer, you need a strong background in data engineering, automation, CI/CD practices, and cloud platforms, typically supported by a degree in computer science or a related field. Familiarity with tools like Jenkins, Docker, Kubernetes, Terraform, and major cloud providers (AWS, Azure, GCP) as well as relevant certifications significantly enhances effectiveness in this role. Strong problem-solving skills, collaboration, and clear communication are essential soft skills for working across teams and addressing fast-changing data needs. These combined abilities ensure smooth data pipeline operations, minimize downtime, and enable efficient, reliable delivery of data-driven solutions.

What are the common day-to-day responsibilities of a Dataops Engineer?

A Dataops Engineer is typically responsible for designing, deploying, and maintaining automated data pipelines that support business analytics and operations. Daily tasks often include monitoring data workflows, troubleshooting pipeline issues, optimizing system performance, and collaborating with data scientists, analysts, and DevOps teams to ensure seamless data delivery. You may also be involved in implementing data quality checks, managing cloud resources, and improving deployment processes. This role is dynamic and fast-paced, requiring both technical expertise and effective cross-team communication. Working as a Dataops Engineer provides the opportunity to work on cutting-edge projects and directly influence data-driven decision-making across the organization.

What does a DataOps engineer do?

A DataOps engineer is responsible for managing and automating data pipelines, ensuring efficient data flow from collection to analysis. They use tools like automation scripts, cloud platforms, and data management frameworks to improve data quality, reliability, and deployment speed in data-driven environments.

What is a DataOps Engineer job?

A DataOps Engineer is responsible for streamlining and automating data workflows, ensuring data quality, and enabling efficient data integration across platforms. They work closely with data scientists, analysts, and engineers to implement CI/CD pipelines, manage data infrastructure, and optimize data delivery processes. Their role involves leveraging tools for orchestration, monitoring, and version control to enhance collaboration and reliability in data operations.

What are the most commonly searched types of Dataops Engineer jobs in Texas? The most popular types of Dataops Engineer jobs in Texas are:
What are popular job titles related to Dataops Engineer jobs in Texas? For Dataops Engineer jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Dataops Engineer jobs? Cities in Texas with the most Dataops Engineer job openings:

$109K - $131K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 4 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.