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Weekend Data Engineer Jobs in Claremont, NH (NOW HIRING)

Senior Database Developer

Lebanon, NH · On-site

$90K - $144K/yr

Provides guidance in data modeling and data warehouse design as well as guidance to define data ... Minimum of 3 years of programming, data management, and/or analytics experience. * Requires hands ...

No Position Purpose The Software Engineer for Advancement is a full-stack developer who designs ... Familiarity with data governance, privacy, and compliance standards (e.g., FERPA, HIPAA, GDPR)

Senior SSL Industrialization Engineer

Hillsborough, NH · On-site

$101K - $138K/yr

Senior SSL Industrialization Engineer Hillsboro, New Hampshire, United States Sense the power of light ams OSRAM is a global leader in innovative light and sensor solutions. "Sense the power of light ...

The role has high guest interaction supporting children's programming, rental operations, guest ... Must be able to work weekends and holidays * Strong communication skills with a wide variety of ...

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Weekend Data Engineer information

See Claremont, NH salary details

$47.2K

$137.7K

$188.4K

How much do weekend data engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for weekend data engineer in Claremont, NH is $137,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,600.00 and $146,000.00 per year, depending on experience, location, and employer.

What is a weekend data engineer?

Weekend Data Engineers are professionals who work primarily on weekends to design, build, and maintain data systems and pipelines. Their responsibilities may include ensuring data flows smoothly between systems, managing databases, and supporting data analytics tasks during off-peak hours. This role is ideal for organizations that need data engineering support outside of standard business hours, such as companies with continuous operations or those processing large volumes of data over weekends. Weekend Data Engineers often collaborate remotely and may be part-time or contract workers.

What are the key skills and qualifications needed to thrive as a weekend data engineer?

To thrive as a Weekend Data Engineer, you need strong proficiency in data modeling, SQL, ETL processes, and programming languages like Python or Scala, typically supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), data warehouse systems (like Redshift or Snowflake), and relevant certifications are often required. Excellent problem-solving, attention to detail, and the ability to work independently during off-hours are standout soft skills. These skills and qualities are crucial for maintaining reliable data pipelines, troubleshooting issues efficiently, and ensuring uninterrupted data services during weekend operations.

What are the typical expectations and work patterns for a weekend data engineer?

As a Weekend Data Engineer, you’ll generally be responsible for maintaining, optimizing, and troubleshooting data pipelines and infrastructure during the weekend hours when production systems still require support. This role often involves monitoring data flows, addressing urgent issues, and ensuring data availability for business needs that operate on a 24/7 basis. You may collaborate remotely with on-call team members or communicate hand-offs to weekday staff, so strong documentation and clear communication are key. Weekend shifts can offer flexibility but may also require independent problem-solving, as fewer team members are available for immediate support.

What is the difference between Weekend Data Engineer vs Part-Time Data Analyst?

AspectWeekend Data EngineerPart-Time Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with data pipelinesBachelor's in related field; skills in data analysis and visualization
Work EnvironmentTech companies, data-driven organizations, remote or on-siteBusiness, marketing, or finance sectors; often remote or part-time
Employer & Industry UsageUsed in industries needing weekend data processing or maintenanceUsed in roles requiring part-time data insights and reporting

The Weekend Data Engineer focuses on building and maintaining data pipelines during weekends, often requiring technical skills and experience with data infrastructure. In contrast, a Part-Time Data Analyst primarily interprets data, creates reports, and provides insights on a flexible schedule. Both roles are suitable for flexible work arrangements but serve different functions within data teams.

Manufacturing Data Analyst (On-Site)

Whelen Engineering

NH • On-site

Full-time

Posted 10 days ago


Whelen Engineering rating

6.4

Company rating: 6.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

137th of 159 rated electronics manufacturers


Job description

Manufacturing Data Analyst (On-Site)
Department: Office NH
Employment Type: Full Time
Location: Charlestown, NH
Description
We are seeking a Manufacturing Data Analyst with a strong operations background to help turn manufacturing, supply chain, quality, maintenance, inventory, and business process data into actionable insights. This role is ideal for someone who understands how operations work across functions and can translate operational questions into reliable data, clear dashboards, and practical recommendations that improve safety, quality, delivery, cost, productivity, and customer service.
Key Responsibilities
  • Analyze operations, manufacturing, supply chain, quality, maintenance, inventory, and customer service data to identify trends, bottlenecks, risks, and improvement opportunities.
  • Develop and maintain dashboards, reports, and scorecards that track key operational metrics such as throughput, yield, scrap, rework, downtime, labor utilization, cycle time, inventory accuracy, schedule attainment, supplier performance, on-time delivery, and customer service levels.
  • Partner with operations leaders, production teams, supply chain, planning, quality, engineering, maintenance, finance, and customer-facing teams to understand business needs and translate them into data-driven solutions.
  • Validate data accuracy, reconcile discrepancies, and document data sources, definitions, assumptions, and refresh processes.
  • Support continuous improvement initiatives by identifying root causes, quantifying opportunities, and measuring the impact of process changes across operational functions.
  • Use data to support capacity planning, labor planning, production scheduling, inventory optimization, supplier performance management, quality improvement, and operational performance reviews.
  • Create clear, concise presentations and recommendations for operations leadership and cross-functional stakeholders.
  • Help improve data collection processes, reporting standards, and analytics workflows across operations.

Skills, Knowledge and Expertise
  • Bachelor's degree in Operations Management, Supply Chain, Engineering, Business Analytics, Data Analytics, Statistics, Information Systems, or a related field; equivalent practical experience may be considered.
  • 3+ years of experience in data analysis, operations analysis, supply chain analytics, manufacturing analytics, quality analytics, industrial engineering, or a similar role.
  • Hands-on experience working in or closely with an operations environment such as manufacturing, supply chain, distribution, quality, planning, or customer operations.
  • Strong proficiency with Microsoft Excel and data visualization tools such as Power BI, Tableau, or similar platforms.
  • Experience using SQL or other querying tools to extract, transform, and analyze data from databases, ERP systems, MES platforms, quality systems, supply chain systems, or other operational systems.
  • Strong understanding of operational metrics, process flows, constraints, tradeoffs, and continuous improvement concepts.
  • Ability to communicate complex data findings in a clear, practical way for both technical and non-technical audiences.
  • Strong attention to detail, problem-solving ability, and comfort working with incomplete or imperfect operational data.

Preferred Qualifications
  • Advanced proficiency with Microsoft Excel, including formulas, pivot tables, data modeling, data validation, and analysis of large operational data sets.
  • Experience building, maintaining, and improving Tableau dashboards, reports, and visualizations for operations, supply chain, quality, or manufacturing teams.
  • Ability to translate operational questions into clear Tableau views, KPIs, filters, and scorecards that support decision-making at multiple levels of the organization.
  • Experience connecting, cleaning, and validating data from ERP, MRP, MES, CMMS, WMS, CRM, quality management systems, or other operational systems.
  • Familiarity with Lean, Six Sigma, value stream mapping, root cause analysis, standard work, or operational excellence practices.
  • Knowledge of operational performance measures such as OEE, downtime, yield, scrap, labor efficiency, capacity, inventory turns, forecast accuracy, supplier performance, cost drivers, and service levels.
  • Experience supporting multi-site operations or complex environments that include manufacturing, supply chain, quality, or distribution functions.
  • Experience evaluating additional analytics, automation, or reporting tools when supported by a clear business need and return on investment.

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