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Senior Data Engineer Jobs in Rochester, NY (NOW HIRING)

Diverse Lynx

Sr. Data Engineer

Rochester, NY · On-site

$104K - $142K/yr

Diverse Lynx is a company seeking a Sr. Data Engineer. The role involves working with multi-cloud environments, Kubernetes, and CI/CD pipelines, while supporting cross-cloud and on-prem ...

Mvphealthcare

Professional, Data Engineer

Rochester, NY

$113K - $135K/yr

The Data Engineer interfaces with Senior Data Engineers. analysts, business customers (internal or external) to gather and define requirements for solutions. Learns data resources and knows when, how ...

Pwc

Data Engineer - Senior Associate

Rochester, NY · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced ...

Pwc

Data Engineer - Senior Associate

Rochester, NY

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Deloitte

AI Data Engineer - Senior Consultant

Rochester, NY · Hybrid

$103K - $141K/yr

As an AI Engineer Senior Consultant , you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets ...

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All JobsData Engineer JobsSenior Data Engineer JobsSenior Data Engineer Jobs in Rochester, NY

Senior Data Engineer information

See Rochester, NY salary details

$79.9K

$124.6K

$172.7K

How much do senior data engineer jobs pay per year?

As of Jun 17, 2026, the average yearly pay for senior data engineer in Rochester, NY is $124,644.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $142,100.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, build, and maintain data infrastructure. Data engineers are essential for managing complex data pipelines, ensuring data quality, and implementing AI models effectively within organizations. Proficiency in programming, cloud platforms, and data management tools remains critical for the role.

What is the highest salary for a senior data engineer?

The highest salaries for senior data engineers can exceed $150,000 to $200,000 annually, especially in high-cost-of-living areas or with extensive experience, advanced skills in cloud platforms, and expertise in big data tools like Spark or Hadoop. Compensation may also include bonuses, stock options, and other benefits depending on the company and location.

What are Senior Data Engineers?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

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

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What engineer makes $500,000 a year?

Senior Data Engineers with extensive experience, advanced skills in data architecture, and expertise in tools like Spark, Hadoop, or cloud platforms can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, or other incentives.

What engineers make $300,000 a year?

Senior Data Engineers and other highly experienced engineering roles in fields like software, machine learning, and cloud infrastructure can earn $300,000 or more annually, especially with advanced skills, certifications, and working in high-demand industries or companies. Compensation often includes base salary, bonuses, and stock options, reflecting expertise and responsibility levels.

What are some common challenges Senior Data Engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

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

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.
What are the most commonly searched types of Data Engineer jobs in Rochester, NY? The most popular types of Data Engineer jobs in Rochester, NY are:
What are popular job titles related to Senior Data Engineer jobs in Rochester, NY? For Senior Data Engineer jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Senior Data Engineer jobs in Rochester, NY look for? The top searched job categories for Senior Data Engineer jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Senior Data Engineer jobs? Cities near Rochester, NY with the most Senior Data Engineer job openings:
Senior Data Engineer jobs near you
Infographic showing various Senior Data Engineer job openings in Rochester, NY as of June 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $124,644 per year, or $59.9 per hour.

Senior Data Engineer - Cloud & AI Platforms - AIRLHV

NavitasPartners

Rochester, NY • On-site, Remote

$40/hr

Full-time

Posted 21 days ago

Job description

Senior Data Engineer – Cloud & AI Platforms

Location: US / Canada (Remote/Hybrid)
Type: Contract / Full-Time

Overview:

We are hiring a Senior Data Engineer to support large-scale data modernization and AI-driven transformation programs. This role focuses on building robust, scalable cloud data platforms and enabling advanced analytics and AI use cases.

Key Responsibilities:

  • Architect and develop scalable data pipelines and cloud-native data solutions
  • Collaborate with data scientists, analysts, and business stakeholders
  • Ensure high performance, data quality, and governance across platforms

Required Skills:

  • Strong experience in data engineering and cloud-based architectures
  • Hands-on expertise with platforms like Databricks, Snowflake, Azure Synapse, or BigQuery
  • Proficiency in AWS, Azure, or GCP environments

Nice to Have:

  • Experience with ML/AI pipelines (Python, PyTorch, MLOps)
  • Exposure to GenAI frameworks such as LangChain or agent-based systems
  • Familiarity with AI governance and compliance standards

For more details reach at resumes@navitassols.com.