1

Senior Dataops Engineer Jobs (NOW HIRING)

Senior Data Engineer

New York, NY · On-site

$160K - $200K/yr

As a Senior Data Engineer at Rearc, you'll be the technical anchor on complex, client-facing data ... You bring a DataOps mindset: CI/CD for data pipelines, automated testing, observability, and ...

Senior Data Engineer

Charlotte, NC · On-site

$103K - $140K/yr

Senior Data Engineer - Data Architecture & Platform CPI Security, a national leader in residential ... DataOps Implementation Enable reliable, scalable, and automated data workflows by implementing ...

Senior Data Engineer

Charlotte, NC · On-site

$103K - $140K/yr

Senior Data Engineer - Data Architecture & Platform CPI Security, a national leader in residential ... DataOps Implementation Enable reliable, scalable, and automated data workflows by implementing ...

Sr Data Engineer

Atlanta, GA

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI ... Implement DataOps practices to ensure continuous integration and delivery of data pipelines ...

Senior Data Engineer

Charlotte, NC · On-site

$103K - $140K/yr

Senior Data Engineer - Data Architecture & Platform CPI Security, a national leader in residential ... DataOps Implementation Enable reliable, scalable, and automated data workflows by implementing ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI ... Implement DataOps practices to ensure continuous integration and delivery of data pipelines ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

As a Senior Data Engineer, you will be part of a high-performing global team delivering advanced AI ... Implement DataOps practices to ensure continuous integration and delivery of data pipelines ...

Senior Data Engineer

Charlotte, NC · On-site

$103K - $140K/yr

Mentor junior engineers on a lean team while personally implementing the solutions you design ... Strong experience with CI/CD & DataOps (pipeline automation, deployment). *Tools/Software:

New

next page

Showing results 1-20

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 Jul 11, 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:
What states have the most Senior Dataops Engineer jobs? States with the most job openings for Senior Dataops Engineer jobs include:
Infographic showing various Senior Dataops Engineer job openings in the United States as of July 2026, with employment types broken down into 7% Locum Tenens, 12% As Needed, 39% Full Time, 2% Contract, 39% Nights, and 1% Summer. Highlights an 63% Physical, 8% Hybrid, and 29% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior IT Data Engineer

Diverse Agile Solutions

Washington, DC • On-site

$70 - $82/hr

Full-time

Re-posted 25 days ago


Job description

Senior IT Data Engineer

Diverse Agile Solutions (DAS)

Location: Washington, D.C. (Hybrid)
Position Type: Full-Time
Citizenship Requirement: U.S. Citizen Required
Client: Federal Reserve Board Division of Research & Statistics (R&S)
Experience Level: Senior (7+ Years)
Security Requirement: Must be eligible to work on Federal projects

About Diverse Agile Solutions (DAS)

At Diverse Agile Solutions (DAS), we deliver innovative technology solutions that help government agencies and commercial organizations modernize operations, improve decision-making, and achieve mission success. We are seeking a highly skilled Senior IT Data Engineer to support the Federal Reserve Board's Data Architecture, Technology, and Analytics (DATA) Section within the Division of Research & Statistics.

This is an exciting opportunity to contribute to the modernization of enterprise data architecture and analytics capabilities that support economic research, policy analysis, and data-driven decision-making at one of the nation's most influential institutions.

Position Overview

The Senior IT Data Engineer will play a critical role in transforming how the Federal Reserve Board's Division of Research & Statistics ingests, organizes, processes, and visualizes data. This position is responsible for designing, developing, and optimizing enterprise data architectures, scalable data pipelines, and advanced analytics platforms that support economists, researchers, and technical teams.

The ideal candidate is a hands-on data engineering professional with deep expertise in data modeling, database architecture, ETL/ELT development, cloud technologies, and enterprise-scale data solutions. This individual will help drive next-generation data initiatives while ensuring efficient, secure, and reliable data delivery across multiple platforms and environments.

Key Responsibilities
  • Design, develop, and maintain enterprise data architectures, databases, and data integration solutions.
  • Build, optimize, and automate scalable ETL/ELT pipelines for structured and unstructured data sources.
  • Develop and maintain high-performance data processing frameworks supporting large-scale analytics workloads.
  • Design conceptual, logical, and physical data models aligned with business and research requirements.
  • Implement and manage data lake, data warehouse, and enterprise data platform solutions.
  • Collaborate with economists, researchers, and technical stakeholders to support data-driven research and policy initiatives.
  • Optimize data flow, storage, and processing architectures for performance, scalability, and reliability.
  • Perform root cause analysis on data and business processes to identify improvement opportunities.
  • Support migration of data pipelines and workflows between on-premises and cloud environments.
  • Develop and maintain DataOps practices, CI/CD pipelines, and automated deployment processes.
  • Ensure adherence to data governance, security, and architectural standards.
  • Evaluate emerging technologies and recommend innovative solutions to improve enterprise data capabilities.
  • Document technical solutions, architecture designs, and operational procedures.
Required QualificationsEducation
  • Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
  • Advanced degree (Master's or Ph.D.) preferred.
Experience
  • Minimum of 7 years of professional experience in Data Engineering, Data Architecture, Database Administration, or related disciplines.
  • Proven experience designing and implementing enterprise-scale data solutions.
  • Experience supporting complex research, analytics, or data-intensive environments.
  • Strong ability to work independently while supporting multiple stakeholders and projects.
Required Technical SkillsData Engineering & Architecture
  • Advanced SQL expertise.
  • Extensive experience with:
    • PostgreSQL
    • Microsoft SQL Server
    • MySQL
  • Data modeling and enterprise information architecture design.
  • Data lake and data warehouse architecture.
  • Change Data Capture (CDC) implementation and maintenance.
  • Data integration and pipeline automation.
Programming & Analytics
  • Advanced proficiency in:
    • Python
    • R
  • Experience with additional programming languages such as:
    • Java
    • Scala
    • JavaScript
    • Perl
Data Processing & Orchestration
  • ETL/ELT workflow development and automation.
  • Distributed computing and large-scale data processing.
  • Workflow orchestration platforms such as:
    • Apache Airflow
    • Prefect
    • Dagster
    • AWS Step Functions
Cloud & Modern Data Platforms
  • Hands-on experience with:
    • AWS
    • Microsoft Azure
    • Snowflake
  • Cloud migration of data pipelines and workflows.
  • Enterprise data platform modernization initiatives.
DevOps & DataOps
  • CI/CD pipeline implementation and support.
  • GitLab and GitHub source control management.
  • Linux-based development environments.
  • Automated testing, deployment, and operational monitoring.
Preferred Qualifications
  • Experience working with economic, financial, or research-oriented data environments.
  • Knowledge of time-series data analysis and forecasting methodologies.
  • Experience with NoSQL databases and graph database technologies.
  • Experience developing, training, deploying, and maintaining machine learning models.
  • Familiarity with advanced analytics, statistical modeling, and predictive analytics.
  • Experience supporting Federal Government agencies or highly regulated organizations.
Desired Competencies
  • Exceptional analytical and problem-solving skills.
  • Strong troubleshooting and root-cause analysis capabilities.
  • Excellent written and verbal communication skills.
  • Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
  • Strong customer-service mindset and collaborative approach.
  • Self-motivated, detail-oriented, and results-driven professional.
Why Join DAS?
  • Work on mission-critical initiatives supporting the Federal Reserve Board.
  • Collaborate with leading economists, researchers, and technology professionals.
  • Contribute to innovative data modernization and analytics programs.
  • Competitive compensation and benefits package.
  • Opportunities for professional growth and career advancement.
  • Hybrid work environment in the Washington, D.C. metropolitan area.
Equal Employment Opportunity

Diverse Agile Solutions (DAS) is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other protected status under applicable federal, state, or local laws.

Apply Today

If you are a highly motivated Data Engineer with a passion for building modern, scalable data solutions and supporting impactful economic research initiatives, we encourage you to apply and join the DAS team supporting the Federal Reserve Board in Washington, D.C.