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Senior Data Analytics Engineer Jobs in Rochester, NY

Quality Data & Analytics Engineer

Fairport, NY

$68.40K - $88.30K/yr

The Division Quality Data & Analytics Engineer bridges industrial engineering, manufacturing, and data systems. Unlike traditional IT roles, this position requires hands-on manufacturing experience ...

Quality Data & Analytics Engineer

Fairport, NY · On-site

$68.40K - $88.30K/yr

The Division Quality Data & Analytics Engineer bridges industrial engineering, manufacturing, and data systems. Unlike traditional IT roles, this position requires hands-on manufacturing experience ...

Quality Data & Analytics Engineer

Fairport, NY

$68.40K - $88.30K/yr

The Division Quality Data & Analytics Engineer bridges industrial engineering, manufacturing, and data systems. Unlike traditional IT roles, this position requires hands-on manufacturing experience ...

This leader is responsible for the day-to-day management and supervision of Quality Engineers and ... Communicate Quality and Compliance strategy, progress, and risk mitigation plans to senior ...

Senior Data Lake Engineer

Farmington, NY · On-site

$104.50K - $142K/yr

Senior Data Lake Engineer/Developer-Tech Lead Duration: 6 months CTH Location: New York Hands-on Tech lead responsible for designing a large Datalake, managing data flows that integrate information ...

New

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 ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager ... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google ...

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Showing results 1-20

Senior Data Analytics Engineer information

See Rochester, NY salary details

$79.9K

$124.7K

$172.7K

How much do senior data analytics engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for senior data analytics engineer in Rochester, NY is $124,677.00, 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.

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

To thrive as a Senior Data Analytics Engineer, you need expertise in statistics, data modeling, and programming languages such as Python or SQL, typically backed by a degree in computer science, engineering, or a related field. Experience with data analytics tools (e.g., Tableau, Power BI), cloud platforms (e.g., AWS, Azure), and relevant certifications like Google Data Engineer are highly valued. Strong problem-solving, communication, and leadership skills help you translate complex data insights into actionable business strategies and mentor junior team members. These capabilities are crucial for delivering accurate data-driven solutions that drive organizational decision-making and innovation.

How does a Senior Data Analytics Engineer typically collaborate with cross-functional teams to deliver insights?

As a Senior Data Analytics Engineer, you will frequently work with stakeholders in product, marketing, and engineering to translate business needs into data solutions. This involves gathering requirements, designing and building data pipelines, and presenting actionable insights. Effective communication and regular meetings with team members ensure that data models and dashboards align with business objectives. You may also mentor junior analysts and engineers, fostering a collaborative and knowledge-sharing environment.

What does a Senior Data Analytics Engineer do?

A Senior Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines and analytical solutions. They work closely with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability. Their role often includes optimizing data workflows, implementing best practices in data management, and mentoring junior team members. Additionally, they help translate business needs into technical solutions to support data-driven decision making.

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

AspectSenior Data Analytics EngineerData Scientist
CredentialsBachelor's/Master's in Data Science, Computer Science, or related fieldsBachelor's/Master's in Data Science, Statistics, or related fields
Work EnvironmentFocus on data pipelines, analytics tools, and reporting systemsFocus on model development, statistical analysis, and predictive modeling
Industry UsageUsed in analytics teams to build data infrastructure and insightsUsed in R&D, product development, and research teams for modeling

While both roles require strong analytical skills and similar educational backgrounds, Senior Data Analytics Engineers primarily focus on building and maintaining data infrastructure and delivering insights through analytics tools. Data Scientists, on the other hand, concentrate on developing predictive models and statistical analysis. The roles often collaborate but serve different functions within data-driven organizations.

What are the most commonly searched types of Data Analytics Engineer jobs in Rochester, NY? The most popular types of Data Analytics Engineer jobs in Rochester, NY are:
What are popular job titles related to Senior Data Analytics Engineer jobs in Rochester, NY? For Senior Data Analytics Engineer jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Senior Data Analytics Engineer jobs in Rochester, NY look for? The top searched job categories for Senior Data Analytics Engineer jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Senior Data Analytics Engineer jobs? Cities near Rochester, NY with the most Senior Data Analytics Engineer job openings:
Quality Data & Analytics Engineer

Quality Data & Analytics Engineer

Corning Incorporated

Fairport, NY • On-site

$108.70K - $130.50K/yr

Full-time

Posted 6 days ago


Corning rating

8.2

Company rating: 8.2 out of 10

Based on 122 frontline employees who took The Breakroom Quiz

80th of 511 rated manufacturers


Job description

Job Summary:
Corning Incorporated is a leading innovator in glass, ceramic, and materials science. They are seeking a Quality Data & Analytics Engineer to bridge industrial engineering, manufacturing, and data systems, transforming fragmented data into actionable insights to improve quality and operations.
Responsibilities:
• Design and manage Power Platform solutions—including Power BI dashboards, PowerApps, and automated workflows—to support QMS and PEX operations.
• Translate complex manufacturing data into clear visualizations for all stakeholders using SalesForce, ETQ, SAP, and MES.
• Identify, assess, and close data gaps — proactively evaluate existing data sources across the quality, identify where critical data is missing, poorly structured, or uncaptured, and engineer new data collection methods, pipelines, and integrations to fill those gaps
• Use an industrial engineering perspective in data analysis by drawing on expertise in manufacturing processes, process control, OEE, yield analysis, cycle time, and reducing variation. This approach helps ensure that analytics results are practical and lead to real improvements in operations.
• Conduct comprehensive data analyses supporting continuous improvement initiatives, collaborating with process engineering and quality teams to identify root causes, track performance trends, and validate improvement outcomes
• Facilitate the integration of quality and production processes within ERP and MES systems to enhance system functionality, streamline data workflows, and improve overall manufacturing performance
• Champion the adoption and adherence to QMS and CI best practices across sites, serving as a subject matter expert (SME) for data-driven decision-making, process optimization, and analytical best practices
• Leverage artificial intelligence (AI) and emerging technologies to innovate, solve complex quality and operational challenges, and continuously advance data accuracy and efficiency across the division
• Lead projects for implementing new QMS, analytics, and continuous improvement software, ensuring seamless integration with existing systems and alignment with evolving business needs — from requirements gathering through go-live and sustainment
• Proactively identify and resolve application-related issues (break/fix), maintaining the reliability, accuracy, and effectiveness of quality and manufacturing data systems across all supported sites
Qualifications:
Required:
• Manufacturing fluency — understanding of manufacturing processes, quality systems, and operational workflows, able to translate floor-level needs into structured data requirements
• Power BI proficiency — advanced skill in developing interactive, multi-source dashboards and reports that communicate complex manufacturing data clearly to diverse audiences
• PowerApps and Power Automate — experienced in building workflow automation and custom applications that support quality and operations teams
• Data source architecture and pipeline development — ability to identify missing data, design new collection structures, and build integrations that bring previously uncaptured information into analytics platforms
• Systems integration knowledge — skilled in connecting and harmonizing data streams from ERP, MES, QMS, and shop floor data collection systems into unified, reliable reporting environments
• Data management — skilled in collecting, cleaning, organizing, and maintaining accurate large-scale manufacturing data sets with high attention to data integrity
• Database systems and data architecture — knowledgeable in relational database concepts, data modeling, and architecture principles that support scalable analytics solutions
• AI and emerging technology adoption — actively utilizes AI tools and new technologies to innovate data workflows, improve accuracy, and solve complex manufacturing and quality challenges
• Project leadership — experienced in managing data and systems projects independently, setting priorities, coordinating cross-functional stakeholders, and delivering results on time
• Cross-functional collaboration — highly effective working partner for process engineering, quality, operations, and IT teams — able to speak the language of the floor and the language of data with equal credibility
• Bachelor's degree in engineering, sciences, management, or arts
• 3-5 years of hands-on experience with manufacturing data systems and processes, including working with ERP, MES, and QMS platforms for data integration, analysis, and reporting.
Preferred:
• Lean / Six Sigma Green Belt or Black Belt — strongly preferred; the ability to apply structured problem-solving and variation reduction methodologies directly enhances the value of this role
• SQL experience — ability to write and modify queries for data extraction, transformation, and validation across relational databases
• Industrial engineering tools and methods — familiarity with time studies, process mapping, OEE frameworks, capacity analysis, or similar IE methodologies as they relate to data collection and analysis
• Experience with shop floor data collection systems — historian platforms, SCADA, or similar real-time manufacturing data sources
• Python or R — basic scripting for data manipulation or automation is a plus
Company:
Corning is a manufacturer of glass, ceramics, and related materials. Founded in 1851, the company is headquartered in Corning, USA, with a team of 10001+ employees. The company is currently Late Stage.

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