ZipRecruiter

Log In

1

Senior Dataops Engineer Jobs (NOW HIRING)

Amtex Enterprises Inc

Senior DataOps Engineer

Charlotte, NC · On-site

$110.21 - $117.10/hr

Senior DataOps Engineer Duration: 12+ Months Rate: $80-85/hr on Vendor W2- MAX Location: Remote or Hybrid (Charlotte, NC) Department: Integration, Data & AI Engineering Position Overview Seeking a ...

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.

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

$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 ...

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 ...

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 ...

Solv Health

NY · On-site

$90 - $120/hr

Hai 4+ anni in un ruolo di data engineering, analytics engineering o DataOps -- con ownership di pipeline da cui altri dipendono * Hai una solida esperienza in SQL e data modeling: hai preso ...

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 ...

Apple Inc.

PART DataOps Engineer

Cupertino, CA · On-site

$118.50 - $197.50/hr

Apple is seeking a senior, hands‑on Data Engineer to join the Next‑Gen Workflow team within our Finance Process, Analytics, Reporting & Technology (PART) Data Operations group. You'll design and ...

Medium

$120 - $150/hr

We are looking for a motivated and adaptive DataOps Engineer, Technical Referent to join our fast ... Collaborative international environment with senior technical leadership. * High autonomy to design ...

New

next page

Showing results 1-20

All JobsTechnology JobsData JobsData Software Engineer JobsSenior Dataops Engineer Jobs

Senior Dataops Engineer information

See salary details

$59.5K

$126.6K

$183.5K

How much do senior dataops engineer jobs pay per year?

As of Aug 22, 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 is a senior DataOps engineer?

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.

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.

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:

What states have the most Senior Dataops Engineer jobs?

States with the most job openings for Senior Dataops Engineer jobs include:

What job categories do people searching Senior Dataops Engineer jobs look for?

The top searched job categories for Senior Dataops Engineer jobs are:

Senior Dataops Engineer jobs near you
Infographic showing various Senior Dataops Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior DataOps Engineer

Amtex Enterprises Inc

Charlotte, NC • On-site

$110.21 - $117.10/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Senior DataOps Engineer

Duration: 12+ Months

Rate: $80-85/hr on Vendor W2- MAX

Location: Remote or Hybrid (Charlotte, NC)

Department: Integration, Data & AI Engineering

Position Overview

Seeking a Senior DataOps Engineer to design, build, automate, and support enterprise-scale data platforms leveraging Databricks and AWS. This role is responsible for developing scalable, high-performing, and governed data pipelines while driving platform automation, Infrastructure as Code (IaC), and DataOps best practices.

The ideal candidate will have extensive experience administering Databricks environments, optimizing platform performance, implementing CI/CD pipelines, and supporting enterprise analytics and AI/ML initiatives.

Key Responsibilities
  • Databricks Platform Engineering & DataOps
  • Design, build, optimize, and support enterprise-scale ETL/ELT pipelines within Databricks.
  • Develop scalable batch and streaming data pipelines using PySpark, Spark SQL, Delta Lake, and Databricks Workflows.
  • Configure and optimize Databricks clusters for performance, scalability, reliability, and cost efficiency.
  • Implement Delta Lake best practices, including partitioning, schema evolution, compaction, optimization, and performance tuning.
  • Administer Unity Catalog, including governance, access controls, auditing, lineage, and security.
  • Design and support Medallion (Bronze, Silver, Gold) Lakehouse architectures.
  • Monitor, troubleshoot, and optimize Databricks jobs, workflows, and platform services.
  • Support enterprise AI/ML and analytics workloads running within Databricks.
  • Cloud Data Engineering
  • Build and maintain scalable data ingestion and transformation pipelines using Python, PySpark, SQL, AWS Glue, and other AWS services.
  • Integrate structured, semi-structured, unstructured, and streaming data from enterprise systems.
  • Develop real-time data processing solutions using AWS Kinesis and Firehose.
  • Partner with architecture, analytics, AI/ML, and engineering teams to deliver enterprise data solutions.
  • Infrastructure Automation & DevOps
  • Implement Infrastructure as Code (IaC) using Terraform to provision and manage Databricks environments and AWS infrastructure.
  • Automate deployments, environment provisioning, configuration management, and operational workflows.
  • Design and maintain CI/CD pipelines supporting Databricks deployments and infrastructure automation.
  • Manage version control repositories and DataOps best practices.
  • Drive platform standardization and deployment consistency across development, test, and production environments.
  • Governance & Operational Excellence
  • Ensure compliance with enterprise security, governance, privacy, and regulatory standards.
  • Implement data quality controls, lineage tracking, auditing, and operational monitoring.
  • Develop operational standards, monitoring frameworks, and support procedures.
  • Provide technical leadership and mentor engineers on DataOps and Databricks best practices.
Required Qualifications
  • 8+ years of experience in Data Engineering, Platform Engineering, or DataOps.
  • 5+ years of hands‑on experience with Databricks in enterprise environments.
  • Strong experience with Python, PySpark, Spark SQL, and SQL.
  • Deep expertise with Delta Lake, Databricks Workflows, Unity Catalog, cluster administration, and performance optimization.
  • Experience designing and supporting Lakehouse/Medallion architectures.
  • Proven experience with Terraform and Infrastructure as Code (IaC).
  • Strong knowledge of CI/CD pipelines and DevOps/DataOps methodologies.
  • Experience with AWS services including AWS Glue, Kinesis, Firehose, S3, and IAM.
  • Strong understanding of data governance, security, observability, and monitoring.
  • Excellent communication, leadership, problem‑solving, and collaboration skills.
Deliverables
  • Production‑ready Databricks ETL/ELT pipelines and workflows.
  • Optimized and governed Databricks platform environments.
  • Terraform modules and Infrastructure as Code automation.
  • Monitoring and observability dashboards for Databricks workloads.
  • Enterprise data models, lineage documentation, and operational runbooks.
  • CI/CD pipelines and deployment automation.
  • Weekly status updates and participation in Agile ceremonies.
#J-18808-Ljbffr

Apply