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Senior Dataops Engineer Jobs (NOW HIRING)

Scout Motors Inc.

Senior DataOps Engineer

Charlotte, NC · On-site

$102K - $140K/yr

The Senior DataOps Engineer will play a crucial role in building a secure and scalable data platform that enables real-time insights and supports AI-enabled use cases across the organization.

Guild

Senior DataOps Engineer

$94K - $136K/yr

Position Summary The Senior DataOps Engineer is responsible for executing the organization's data management and storage system strategy ensuring timely access to secure, resilient, scalable, and ...

Voyager Technologies, Inc.

Senior DataOps Engineer

$107K - $146K/yr

Job Summary The DataOps Engineer is responsible for designing, building, and operationalizing data infrastructure that powers the organization's analytics and business intelligence capabilities. This ...

Scout Motors

Senior DataOps Engineer

Charlotte, NC · On-site

$119K - $157K/yr

Bachelor's degree in computer science, information technology, or related field or equivalent work experience. * 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive ...

Scout Motors

Senior DataOps Engineer

Charlotte, NC · On-site

$102K - $140K/yr

Bachelor's degree in computer science, information technology, or related field or equivalent work experience. * 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive ...

MM International

Data Engineer with DevOps Skill

Dearborn, MI · On-site

$105K - $126K/yr

Teams Video interview 1 hour - 1 round · We are seeking a highly skilled and experienced Senior DataOps Engineer to join our EPEO DataOps team. · This role will be pivotal in designing, building ...

PayNearMe, Inc.

DataOps Engineer

Santa Clara, CA · On-site +1

$120K - $150K/yr

We're looking to add a dynamic DataOps Engineer , reporting to our Manager of Data Operations ... Responsibilities: * Assist senior engineers in the design of data models and schemas, and ...

Fractal

Senior Data Ops Engineer

New York, NY · On-site

$125K - $150K/yr

Role Overview We are hiring a Senior DataOps Engineer to drive enterprise DataOps capabilities, ensuring reliable, scalable, and production-ready data pipelines on Azure Databricks platforms. This ...

Analytica

Senior Data Engineer

Washington, DC · On-site

$119K - $162K/yr

The ideal candidate possesses deep expertise in cloud-native data engineering, DataOps practices, and regulated healthcare environments. The Senior Data Engineer will lead the development and ...

Analytica

Senior Data Engineer

Washington, DC · On-site

$120K - $163K/yr

The ideal candidate possesses deep expertise in cloud-native data engineering, DataOps practices, and regulated healthcare environments. The Senior Data Engineer will lead the development and ...

Judge Group, Inc.

Senior Data Engineer

Dallas, TX · On-site

$120K - $130K/yr

Senior Data Engineer About the Role We are seeking a Senior Data Engineer to design, build, and ... Apply DataOps, CI/CD, governance, security, and operational best practices across the data ...

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Senior Dataops Engineer information

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$59.5K

$126.6K

$183.5K

How much do senior dataops engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for senior dataops engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What are some common challenges a Senior DataOps Engineer faces when scaling data infrastructure for a growing organization?

A Senior DataOps Engineer often encounters challenges such as ensuring data pipeline reliability during rapid scaling, managing increasing data volume and complexity, and maintaining high data quality across distributed environments. Balancing automation with flexibility, integrating new tools with legacy systems, and coordinating with cross-functional teams (like data scientists and DevOps) are also key hurdles. Success in this role requires proactively identifying bottlenecks, optimizing workflows, and fostering a culture of collaboration to support evolving business needs.

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

To thrive as a Senior DataOps Engineer, you need a solid background in data engineering, automation, CI/CD pipelines, and strong knowledge of data architecture, usually supported by a degree in computer science or a related field. Expertise in tools like Apache Airflow, Kubernetes, Docker, cloud platforms (AWS, Azure, or GCP), and proficiency with scripting languages such as Python or Bash are typically required, along with certifications like AWS Certified Solutions Architect or Google Cloud Data Engineer. Outstanding problem-solving skills, collaboration, and effective communication are essential soft skills for integrating diverse teams and managing complex workflows. These capabilities ensure data reliability, streamlined operations, and scalable solutions in dynamic data-driven environments.

What is the difference between Senior Dataops Engineer vs Data Engineer?

AspectSenior Dataops EngineerData Engineer
CredentialsTypically requires experience with cloud platforms, scripting, and data pipeline toolsRequires knowledge of database systems, SQL, and data modeling
Work EnvironmentFocuses on deployment, automation, and maintaining data infrastructureDesigns and builds data pipelines and storage solutions
Industry UsageCommon in organizations emphasizing data operations and automationWidespread across industries for data storage and processing

The main difference is that Senior Dataops Engineers focus on managing and automating data workflows and infrastructure, while Data Engineers primarily design and build data pipelines and storage systems. Both roles require strong technical skills, but their focus areas differ within the data ecosystem.

What are Senior DataOps Engineers?

Senior DataOps Engineers are experienced professionals who design, implement, and manage data pipelines and workflows to ensure reliable, efficient, and scalable data operations within an organization. They bridge the gap between data engineering, DevOps, and analytics by automating data integration, deployment, and monitoring processes. Their role often includes optimizing data infrastructure, ensuring data quality, and enabling data teams to quickly deliver insights. Senior DataOps Engineers also mentor junior team members and help define best practices for data operations.
More about Senior Dataops Engineer jobs
What cities are hiring for Senior Dataops Engineer jobs? Cities with the most Senior Dataops Engineer job openings:
What are the most commonly searched types of Dataops Engineer jobs? The most popular types of Dataops Engineer jobs are:
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Senior Dataops Engineer jobs near you
Infographic showing various Senior Dataops Engineer job openings in the United States as of July 2026, with employment types broken down into 5% Locum Tenens, 17% Internship, 9% As Needed, 35% Full Time, 2% Contract, and 32% Nights. Highlights an 61% Physical, 11% Hybrid, and 28% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior DataOps Engineer

Scout Motors Inc.

Charlotte, NC • On-site

$102K - $140K/yr

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Scout Motors Inc. is dedicated to carrying forward the heritage of iconic American vehicles while embracing innovation. The Senior DataOps Engineer will play a crucial role in building a secure and scalable data platform that enables real-time insights and supports AI-enabled use cases across the organization.
Responsibilities:
• Contribute to the design, implementation, automation, maintenance, and operational support of enterprise-scale cloud data platforms leveraging Databricks, AWS cloud services, and modern Infrastructure as Code (IaC) practices.
• Lead the design, development, optimization, and operational management of enterprise-scale ETL/ELT pipelines within Databricks.
• Build and maintain scalable batch and streaming data pipelines using PySpark, Spark SQL, Delta Lake, and Databricks Workflows.
• Configure, optimize, and manage Databricks clusters for performance, scalability, reliability, and cost efficiency.
• Work closely with software development and systems teams to build Data Integration solutions.
• Design and build Data models using tools such as Lucid, Talend, Erwin, MySQL workbench.
• Define and enhance enterprise data model to reflect relationships and dependencies.
• Review application data systems to ensure adherence to data governance policies.
• Design and build ETL (Python), ELT(Python) infrastructure, automation, and solutions to transform data as required.
• Design and Implement BI dashboards to visualize Trends and Forecasts.
• Design and implement data infrastructure components, ensuring high availability, reliability, scalability, and performance.
• Design, train and deploy ML models
• Implement monitoring solutions to proactively identify and address potential issues.
• Collaborate with security teams to ensure the data platform meets industry standards and compliance requirements.
• Collaborate with cross-functional teams, including product managers, developers, and business partners to ensure robust and reliable systems.
Qualifications:
Required:
• Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
• 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive environment.
• Experience with streaming and event-based architecture.
• Experience implementing data lakehouse solutions using Databricks.
• Experience with infrastructure as code (Terraform).
• Proficient in building data pipelines using languages such as Python and SQL.
• Experience with AWS based data services such as Glue, Kinesis, Firehose or other comparable services.
• Experience with Structured, unstructured and time series databases.
• Solid understanding of cloud data storage solutions such as RDS, DynamoDB, DocumentDB, Mongo, Cassandra, Influx.
• Several years of experience working with cloud platforms such as AWS and Azure.
• Proven ability to develop and deploy scalable ML models.
• Hands-on experience in designing, training, and deploying ML models.
• Strong ability to extract actionable insights using ML techniques.
• Ability to leverage ML algorithms for forecasting trends and decision-making.
• Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
• Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.
Company:
Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work. Founded in 2022, the company is headquartered in Washington, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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