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Senior Dataops Engineer Jobs in Boston, MA (NOW HIRING)

Director Product Engineering

Norwell, MA · On-site

$245K - $257K/yr

Hands-on familiarity with Azure, GitHub, DevOps pipelines, API design, DataOps, OpenAI/GenAI ... Stakeholder Engagement Own communications with SteerCo, senior business sponsors, and peer platform ...

Director Product Engineering

Norwell, MA · On-site

$245K - $257K/yr

Hands-on familiarity with Azure, GitHub, DevOps pipelines, API design, DataOps, OpenAI/GenAI ... Stakeholder Engagement Own communications with SteerCo, senior business sponsors, and peer platform ...

Stakeholder Engagement • Own communications with SteerCo, senior business sponsors, and peer ... Hands-on familiarity with Azure, GitHub, DevOps pipelines, API design, DataOps, OpenAI/GenAI ...

Director Product Engineering

Norwell, MA

$245K - $257K/yr

Hands-on familiarity with Azure, GitHub, DevOps pipelines, API design, DataOps, OpenAI/GenAI ... Stakeholder Engagement Own communications with SteerCo, senior business sponsors, and peer platform ...

Senior Dataops Engineer information

See Boston, MA salary details

$64.6K

$137.5K

$199.4K

How much do senior dataops engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for senior dataops engineer in Boston, MA is $137,492.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $155,900.00 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.

What are popular job titles related to Senior Dataops Engineer jobs in Boston, MA?

For Senior Dataops Engineer jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Senior Dataops Engineer jobs in Boston, MA look for?

The top searched job categories for Senior Dataops Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Senior Dataops Engineer jobs?

Cities near Boston, MA with the most Senior Dataops Engineer job openings:

Senior Analyst, Data Engineering

Dell, Inc.

Hopkinton, MA • On-site

$102K - $132K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description


Sr. Analyst, Data Engineering
Data Engineering is the practice of designing, building, and maintaining systems that collect, store, process, govern, and analyze large volumes of data required by analysts, data scientists, and AI/ML applications. It serves as the foundation for enabling data-driven insights, intelligent automation, and AI-powered decision-making across the organization.
What You'll Achieve
Data Management, Engineering & AI Enablement - ETL/ELT processing, data transformation, data quality, governance, security, and AI-ready data architectures across enterprise platforms. You will help enable trusted, high-quality data to support analytics, reporting, machine learning, agentic AI solutions, and operational decision-making.
Responsibilities
You Will:
Data Migration & Mapping: Analyze source and target database structures, identify data dependencies, constraints, and transformation needs, and create source-to-target mapping documents with defined transformation rules and business logic in collaboration with stakeholders
Data Pipeline Design & Architecture: Work with structured and unstructured data to design and implement scalable data pipelines that support analytics, AI, and machine learning workloads, aligning schemas, relationships, and data models with data architects
Data Quality & Governance: Develop processes to improve data quality, observability, lineage, and governance while ensuring data platforms comply with enterprise security, privacy, and responsible AI standards
AI/ML Enablement & Agentic AI Support: Partner with data scientists, AI engineers, and business teams to enable trusted datasets for AI/ML model development and support implementation of data solutions for Agentic AI use cases
AI-Driven Development & Automation: Leverage AI-assisted development tools to improve productivity and documentation quality, and evaluate opportunities for intelligent automation using AI and machine learning techniques within data engineering processes
Qualifications
Essential Requirements:
Databases & SQL: Proficiency in Teradata, PostgreSQL, and SQL for querying, transforming, profiling, and validating data, with a strong understanding of relational, dimensional, and analytical data models to accurately map source-to-target schemas
ETL/ELT & Development Practices: Experience with Informatica, Apache Airflow, or comparable data integration platforms, along with familiarity with version control and CI/CD practices using Git-based development workflows
Programming & Automation: Proficiency in Python for automation, orchestration, and custom data solutions, with the ability to manage unexpected data quality issues, platform constraints, and migration challenges with agility
Data Quality & Governance: Understanding of data lineage, metadata management, master data management (MDM), and governance concepts to ensure data integrity and compliance throughout the data lifecycle
AI-Ready Data Engineering: Knowledge of data preparation, feature engineering concepts, and dataset management for AI/ML workloads, enabling trusted and well-governed datasets for advanced analytics and model development
Desirable Requirements:
Analytics, Reporting & Modern Data Platforms: Knowledge of Power BI or other visualization tools, experience with Airflow, enterprise schedulers, SSIS, SSRS, and Tabular OLAP/semantic modeling, along with understanding of MLOps, DataOps, cloud-native data services, modern lakehouse architectures, and data observability/automated anomaly detection solutions
AI & Intelligent Automation: Exposure to machine learning and AI technologies for automation and operational efficiency, including familiarity with Agentic AI concepts (LLMs, prompt engineering, vector databases, semantic search, responsible AI/AI governance), experience using AI-powered productivity tools such as GitHub and Devin, and understanding of modern AI-driven development practices
Compensation
Dell is committed to fair and equitable compensation practices. The salary range for this position is $102,000 - $132,000.
Benefits and Perks of working at Dell Technologies
Your life. Your health. Supported by your benefits. You can explore the overall benefits experience that awaits you as a Dell Technologies team member - right now at MyWellatDell.com
About Us
Who We Are
We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you.
Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.
Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy.
Visit our Culture Code page to learn more about how we work and lead.

DELL logo

About DELL

Sourced by ZipRecruiter

Dell Technologies helps organizations and individuals build a brighter digital tomorrow. Our company is made up of more than 150,000 people, located in over 180 locations around the world. We're proud to be a diverse and inclusive team and have an endless passion for our mission to drive human progress.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Round Rock, TX, US

Year founded

1984