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Manufacturing Data Analytics Jobs in New York (NOW HIRING)

Data Analytics Engineer

Farmingdale, NY · On-site

$115K - $130K/yr

As a US based manufacturing company, we pride ourselves on high automation machinery and innovative ... The Business Intelligence team is looking for a hands-on Data Analytics Engineer to help build ...

Data Analytics Engineer

Farmingdale, NY · On-site

$115K - $130K/yr

As a US based manufacturing company, we pride ourselves on high automation machinery and innovative ... The Business Intelligence team is looking for a hands-on Data Analytics Engineer to help build ...

Data Analyst - Automotive

New York, NY · Remote

$100K - $120K/yr

If so, we have an exciting opportunity for you to join a forward-thinking Manufacturing Engineering ... Relevant Data Engineering, Data Analytics, or STEM qualifications. Why Join Us? This is an ...

Data Analyst - Automotive

New York, NY · Remote

$100K - $120K/yr

If so, we have an exciting opportunity for you to join a forward-thinking Manufacturing Engineering ... Relevant Data Engineering, Data Analytics, or STEM qualifications. Why Join Us? This is an ...

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Manufacturing Data Analytics information

What is manufacturing data analytics?

Manufacturing data analytics refers to the use of data analysis tools and techniques to collect, interpret, and leverage data generated during manufacturing processes. This approach helps companies identify inefficiencies, predict equipment failures, optimize production, and improve product quality. By analyzing data from sensors, machines, and other sources, manufacturers can make informed decisions that boost productivity and reduce costs. Overall, manufacturing data analytics is key for driving digital transformation and competitiveness in the manufacturing industry.

How do manufacturing data analytics professionals collaborate with production and engineering teams to drive process improvements?

Manufacturing Data Analytics professionals work closely with production and engineering teams by analyzing process data, identifying inefficiencies, and presenting actionable insights. They often participate in cross-functional meetings, where they translate complex data findings into practical recommendations for process optimization, quality improvement, or cost reduction. Effective communication and a collaborative approach are essential, as these professionals must understand operational challenges and ensure data-driven solutions are feasible and aligned with business goals.

What are the key skills and qualifications needed to thrive in manufacturing data analytics, and why are they important?

To thrive in Manufacturing Data Analytics, you need a strong background in statistics, data analysis, and manufacturing processes, often supported by a degree in engineering, data science, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), programming languages like Python or R, and ERP/MES systems is typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex insights clearly are essential soft skills. These competencies enable professionals to drive process improvements, optimize production, and support data-driven decision-making in manufacturing environments.

What is the difference between Manufacturing Data Analytics vs Manufacturing Data Engineer?

AspectManufacturing Data AnalyticsManufacturing Data Engineer
Primary FocusAnalyzing manufacturing data to improve processes and decision-makingDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsData analysis, statistical skills, knowledge of manufacturing processes, often with certifications in data analytics or related fieldsData engineering, programming (Python, SQL), cloud platforms, database management
Work EnvironmentCollaborates with manufacturing teams, data teams, and managementWorks with IT, data teams, and software engineers to develop data systems
Industry UsageUsed across manufacturing sectors for process optimizationSupports manufacturing analytics by providing data infrastructure

Manufacturing Data Analytics focuses on interpreting manufacturing data to enhance operations, while Manufacturing Data Engineers develop and maintain the data systems that enable such analysis. Both roles are essential in manufacturing data-driven strategies but differ in their core responsibilities and skill sets.

What job categories do people searching Manufacturing Data Analytics jobs in New York look for?

The top searched job categories for Manufacturing Data Analytics jobs in New York are:

What cities in New York are hiring for Manufacturing Data Analytics jobs?

Cities in New York with the most Manufacturing Data Analytics job openings:

Infographic showing various Manufacturing Data Analytics job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

$115K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

Overview

D'Addario & Company is the largest manufacturer and distributor of musical instrument accessories in the world. As a US based manufacturing company, we pride ourselves on high automation machinery and innovative technology, as well as our commitment to environmentally sustainable practices. Through our work with the D'Addario Foundation we are committed to helping make music education accessible and ensuring hundreds of thousands of students can participate in music-making programs worldwide, regardless of instrumentation, genre, or life circumstance. Most importantly, we pride ourselves on our diverse team of individuals who commit to the embodiment of our core values of curiosity, passion, candor, family and responsibility and translate them into action every day.

The Business Intelligence team  is looking for a hands-on Data Analytics Engineer to help build, transform, and optimize D'Addario's global data infrastructure. In this role, you'll design and maintain production-grade data pipelines while modeling the clean, well-tested, and documented datasets that power reporting and self-service analytics across the company. You'll work closely with the Global Director of BI and our analysts to turn raw data into reliable, business-ready data products. 

This is an ideal opportunity for an engineer who thrives at bringing data into order, enjoys solving complex data challenges, and is passionate about enabling organizational data intelligence. 

At D'Addario, we don't just offer a job-we offer a career with one of the most iconic names in the music industry. We're passionate about innovation, craftsmanship, and creating a workplace where diverse backgrounds, perspectives, and ideas thrive.  We're eager to connect with individuals who bring fresh thinking and a collaborative spirit. If you're ready to make an impact, we'd love to hear how you'll add value to our team.

Some Perks & Benefits of Working at D'Addario:

  • 401(k) Retirement Plan: Once eligible, D'Addario provides an employer Safe Harbor contribution of 3% of total annual earnings, with the opportunity to earn up to an additional 7% in employer Discretionary contributions, regardless of employee contribution level
  • Health, vision, and dental insurance
  • 12 weeks of fully paid parental leave
  • Fertility and family-building benefits
  • Annual performance and compensation reviews
  • Career pathing and professional development via LinkedIn Learning
  • A generous allotment of Paid Time Off (PTO) days
  • Flexible sick day policy
  • 12 paid holidays
  • Life and AD&D insurance
  • Enhanced short-term disability insurance
  • Employee Assistance Program (EAP)
  • Tuition reimbursement
  • Discounts on D'Addario products and merchandise
  • Company jam nights, artist performances, holiday parties, and special events
  • A passionate, talented team that loves what they do!

Compensation: 

We offer a competitive total compensation package. The base salary range for this role is $115,000-$130,000 and is commensurate with experience, skills, and qualifications. This position is eligible for a discretionary annual bonus, in accordance with company policy.

Responsibilities
  • Build & Optimize Pipelines: Design, implement, and maintain robust, high-performance ELT/ETL data pipelines within Microsoft Fabric and our broader data environment. 
  • Data Integration: Connect and harmonize new data sources-including ERP, e-commerce platforms, and external APIs-into a centralized data platform. 
  • Analytics Data Modeling: Transform raw data into clean, well-structured dimensional models, data marts, and reusable datasets (star schemas) that are analysis-ready for reporting and self-service BI. 
  • Semantic Layer & Metrics: Build and maintain semantic models and standardized metric definitions in Power BI and Microsoft Fabric so the business works from a single, trusted source of truth. 
  • Data Quality & Testing: Implement automated testing, validation, and monitoring to ensure pipelines and datasets are accurate, reliable, and well-documented. 
  • Collaboration: Partner with analysts and stakeholders across Sales, Marketing, Operations, and Product to translate business requirements into reliable data products. 
  • Continuous Improvement: Follow and help improve team standards for coding, documentation, version control, and DataOps across our data engineering and analytics workflows. 
Qualifications
  • 3+ years of hands-on experience as a Data Engineer, Analytics Engineer, or equivalent 
  • Experience building and maintaining production-grade data pipelines and analytics data models 
  • Proficiency in Python, PySpark, and SQL 
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience) 
  • Preferred experience with Microsoft Fabric, Azure Synapse, or Azure Data Lake 
  • Preferred experience implementing DataOps best practices and building transformation models with dbt or similar frameworks 
  • Familiarity with API integrations and third-party data ingestion 
  • Knowledge of data governance and data quality frameworks 
  • Musician or passion for music a plus 

Knowledge, skills, & abilities: 

  • Strong programming in Python and PySpark for data processing and transformation 
  • Advanced SQL and dimensional data modeling (e.g., star schema / Kimball) for analytical performance and scalability 
  • Experience building and maintaining ELT/ETL pipelines and transformation layers, including automated testing and validation of analysis-ready datasets 
  • Strong understanding of cloud data platforms (Azure preferred) 
  • Excellent communication skills with the ability to simplify complex technical concepts 
  • Familiarity with semantic modeling and BI tools such as Power BI and Microsoft Fabric 
  • Self-directed, highly organized, and comfortable operating in a fast-paced, evolving environment 
  • Passion for innovation and leveraging data to create business impact 

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Employment Type: FULL_TIME