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Junior Data Analytics Engineer Jobs in Rochester, NY

We are continuously looking for entry-level software programmers, Java full stack developers, Python/Java developers, data analysts/data scientists, data engineers, machine learning engineers for ...

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 Data Analysts and is also accountable for developing talent, strengthening scientific and compliance ...

... Analyzing complex issues to create innovative solutions - Mentoring and guiding junior team members ... Data Engineer Associate] is a plus - Designing and implementing thorough data architecture ...

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

Data Solutions Engineer

Rochester, NY · On-site +1

$91.53K - $156.50K/yr

Work closely with internal teams, including data engineers, data scientists, analytics engineers and business stakeholders, to understand platform solution needs. Mentor junior engineers, providing ...

This role provides mentorship to junior analysts. Responsibilities Collect, cleanse, transform, and ... Validate and quality-check data sources, queries, and visualizations to ensure accuracy ...

This role provides mentorship to junior analysts. Responsibilities Collect, cleanse, transform, and ... Validate and quality-check data sources, queries, and visualizations to ensure accuracy ...

This role provides mentorship to junior analysts. Responsibilities Collect, cleanse, transform, and ... Validate and quality-check data sources, queries, and visualizations to ensure accuracy ...

This role provides mentorship to junior analysts. Knowledge, Skills and Abilities: Required: * 1-3+ years of experience in SQL, including queries, joins, transformations, and data aggregation. * 1-3+ ...

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Junior Data Analytics Engineer information

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$33.1K

$70.8K

$108K

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

As of May 28, 2026, the average yearly pay for junior data analytics engineer in Rochester, NY is $70,842.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,900.00 and $78,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Junior Data Analytics Engineer, you need a solid understanding of data analysis, statistics, and programming languages such as Python or SQL, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (e.g., Tableau, Power BI), database management systems, and cloud platforms is commonly expected. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in this role. These abilities are crucial for accurately analyzing data, translating findings into actionable insights, and enabling data-driven decision-making within organizations.

What are the most common challenges faced by a Junior Data Analytics Engineer when transitioning from academic projects to real-world business data?

One of the most common challenges for Junior Data Analytics Engineers is adapting to the complexities of real-world data, which is often incomplete, inconsistent, or unstructured compared to clean academic datasets. Additionally, there is a stronger emphasis on collaboration with cross-functional teams and communicating findings to non-technical stakeholders. Learning to balance technical analysis with business objectives, and managing multiple tasks or project deadlines, are also typical hurdles. Overcoming these challenges helps junior engineers grow quickly and become valuable contributors to their teams.

What is a Junior Data Analytics Engineer?

A Junior Data Analytics Engineer is an entry-level professional who assists in collecting, processing, and analyzing data to help organizations make informed decisions. They typically work with data pipelines, databases, and analytical tools to support senior data engineers and analysts. Their responsibilities often include cleaning data, writing basic queries, and creating simple reports or dashboards. This role serves as a foundation for more advanced positions in data engineering and analytics.

What is the difference between Junior Data Analytics Engineer vs Data Analyst?

AspectJunior Data Analytics EngineerData Analyst
Required SkillsBasic programming, data modeling, SQL, data pipeline understandingData visualization, statistical analysis, Excel, SQL
Work EnvironmentCollaborates with data engineers and developers, often in tech or finance sectorsWorks with business teams to interpret data, in various industries
CertificationsSQL, Python, entry-level data certificationsExcel, Tableau, Power BI certifications

Junior Data Analytics Engineers focus on building data pipelines and integrating data systems, requiring programming skills. Data Analysts primarily interpret data through visualization and statistical methods. Both roles often overlap but serve different core functions within data teams.

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 Junior Data Analytics Engineer jobs in Rochester, NY? For Junior Data Analytics Engineer jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Junior Data Analytics Engineer jobs in Rochester, NY look for? The top searched job categories for Junior Data Analytics Engineer jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Junior Data Analytics Engineer jobs? Cities near Rochester, NY with the most Junior Data Analytics Engineer job openings:
Infographic showing various Junior Data Analytics Engineer job openings in Rochester, NY as of May 2026, with employment types broken down into 3% As Needed, 73% Full Time, 17% Part Time, and 7% Contract. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution, with an average salary of $70,842 per year, or $34.1 per hour.
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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