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Manufacturing Data Analytics Jobs in Summit, NJ (NOW HIRING)

My Remote Jobz

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 ...

My Remote Jobz

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 Summit, NJ look for?

The top searched job categories for Manufacturing Data Analytics jobs in Summit, NJ are:

Manufacturing Data Analytics jobs near you
Infographic showing various Manufacturing Data Analytics job openings in Summit, NJ as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Analyst ::New jersey city (NJ) (Onsite)

Talent Movers

Jersey City, NJ • On-site

Contractor

Re-posted 20 days ago

Job description

Role:: Data Analyst

Location :: new jersey city (NJ)  (Onsite)

Rate :: on C2C

Mandatory Skill :: Analyst. ERP, Data Modeling, GCP, SQL, Manufacturing, Data Lake

Key Responsibilities

  • Requirement Gathering & Mapping: Partner with Sales, Finance, and Operations SMEs to understand business requirements, identify critical data elements, and document source-to-target mappings (STTM) for the GCP Data Lake.
  • Canonical Data Modeling: Collaborate with SMEs and data architects to define and document the enterprise canonical model, ensuring standard definitions, naming conventions, and data types across different domains.
  • Technical Specifications: Translate business logic and KPIs into rigorous technical requirements, user stories, and acceptance criteria for the GCP Data Engineering team.
  • Gap & Impact Analysis: Profile source data to identify data quality issues, anomalies, and structural gaps between legacy sources and the target canonical model.
  • KPI & Data Validation: Define the testing and validation criteria to ensure that migrated data accurately populates downstream business KPIs. Perform UAT (User Acceptance Testing) to sign off on engineered data pipelines.
  • Data Governance & Documentation: Maintain the data dictionary, business glossary, and lineage metadata within our data catalog tool (e.g., GCP Dataplex)

Required Skills & Qualifications

  • Experience: 10+ years of experience as a Data Analyst, Business Systems Analyst, or Data Product Owner, with a proven track record in Data Lake, Data Warehouse, or MDM (Master Data Management) implementations.
  • Domain Knowledge: Proven experience working with data domains in Sales (e.g., CRM, pipelines), Finance (e.g., ERP, general ledger), and/or Operations.

 Technical Skills:

  • Advanced SQL: Ability to write complex queries to profile data, analyze schemas, and validate pipeline outputs.
  • Data Modeling: Solid understanding of data modeling concepts (e.g., Star Schema, Snowflake, Inmon vs. Kimball, and Canonical/Universal modeling).
  • Cloud Exposure: Familiarity with cloud data concepts. Direct experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataplex) is highly preferred