Automation & Data Analyst

Overview

JOLLY CLAMPS PVT. LTD.

Manufacturers of Steel Clamps & Couplings

JOB DESCRIPTION

Position

Automation & Data Analyst (Manufacturing Operations)

Department

Automation & Systems

Location

Goregaon (Head Office) + Virar (Factory) — travel between both required

Experience

1–2 years

Reports To

Chief Financial Officer (CFO)

Employment

Full-time, on-site

About the Role

Jolly Clamps Pvt. Ltd. (JCPL) is building in-house capability to automate its manufacturing operations and bring its inventory, work-in-progress (WIP) and costing data under tight, reliable control. This is a hands-on role for someone in their career who wants to excel in how a real manufacturing business runs and turn its day-to-day data into dependable dashboards, reports and small applications.

You will work closely with the Chief Financial Officer (CFO), the operations and information technology (IT) teams, and the shop floor across both the Goregaon head office and the Virar factory. Full training and mentoring will be provided; what matters most is a genuine appetite to learn, attention to detail, and comfort working with data.

Core principles you will be trained to follow:

• rely on a single, agreed source of data rather than scattered reports;
• use clear, deterministic (rule-based) computation that anyone can audit, with no guesswork;
• always validate a solution on one test case before scaling it across the plant.

Key Responsibilities

Under the guidance of the CFO and senior team members, you will support, build and maintain the following. You are not expected to do all of this on day one — you will be brought up to speed project by project.

Production Planning & Control (PPC) — Python-based Planning Solutions

A central part of the role is helping build and run a suite of Python-based tools that turn the monthly Sales forecast into a realistic, committed production plan. Working with the planning and operations teams, you will support:

• Planning engine (demand to commitment): Build and maintain the monthly planning engine that converts the Sales forecast (received item-wise and family-wise from the enterprise resource planning system) into a deliverable commitment, running demand against line capacity, manpower and material limits to produce the family-wise quantity committed to Sales.
• Forecast cleanup & common-part master: Automate cleanup and filtration of the location-wise forecast by grouping stock-keeping units (SKUs) that share a common internal part code into a single common part, replacing the manual pivot; create and maintain the master that maps customer and location SKUs to the common-part code.
• Capacity, manpower & occupancy model: Automate the family-wise line-capacity and manpower model to compute shift-wise occupancy percentage, flag demand exceeding both shifts as over-capacity, and base commitments on current manpower, allowing for the recruitment lead time.
• Economic batch quantity batching: Hold the economic batch quantity (EBQ) per item as a clean master and build batching logic that defaults to it, quantifying the efficiency loss when priority orders break the batch and trigger extra changeovers.
• Make-to-stock stock-level prioritisation: Automate the colour-coded make-to-stock , stock-level sheet and auto-sequence production so the most critical parts are made first, replacing the heavy manual spreadsheet.
• Trading-conversion & excess-production traceability: Build logic that traces production booked against a common part, the trading-conversion transfers to individual customer codes and the residual balance, so excess production is attributed to the Sales order that drove it and made visible to Sales.
• Demand cadence by customer type: Encode the differing demand cadences by customer type (aftermarket weekly; regular original-equipment-manufacturer customers on a weekly cycle; trigger-based customers daily) into the plan, along with the buffer and overtime catch-up mechanism used to meet the required daily rate.
• Material requirement planning: Extend the planning engine to derive raw-material and child-part requirements from the committed family and item plan and batch quantities, so procurement is driven by the confirmed plan and checked against stock and open purchase orders.

Data Reconciliation & Control Reports (rule-based, auditable)

• Daily inventory reconciliation reports (opening stock plus purchases, less consumption, equals closing stock; and finished goods produced versus dispatched).
• Material-balance checks that reconcile input against output, scrap and work-in-progress (WIP) movement, allowing for normal process weight and measurement tolerances.
• Consumption-based costing reports that value material on actual usage rather than purchases, organised by cost centre.
• Reclassification of items between make-to-stock and make-to-order based on demand trends.
• Exception and error-tracking reports that flag wrong, reversed, delayed or duplicate transactions, along with their likely cause.
• Threshold-based monitoring (for example, inventory or work-in-progress above an agreed reference level) with automatic alert notifications.

Workflow Automation

• Help set up the scheduled extraction of system reports, with automatic pickup and processing into daily reconciliations.
• Support automated report extraction through application programming interfaces (API) feeding business intelligence (BI) dashboards.
• Assist in consolidating overlapping automation tools onto a single, governed workflow platform.

Data-Capture Applications & Dashboards

• Support data-capture applications that record activity at source (plan versus actual, productivity, adherence), with a database behind them and a link to the enterprise resource planning (ERP) system.
• Help deploy point-of-source data capture using fixed screens or tablets feeding a central database and live dashboards.

System Controls (with the IT team)

• Help implement controls that prevent item, grade or master-data mismatch, with daily exception reporting.
• Support duplicate-entry prevention using unique transaction identifiers and a holding area for failed entries.
• Assist in evaluating a warehouse management system (WMS) and its integration with the ERP.

General

• Validate every report and tool against real data before it is relied upon.
• Document what you build so others can understand and maintain it.
• Coordinate with stores, shop-floor, accounts and IT colleagues to keep data accurate and on time.

Skills & Knowledge

Essential (foundational level is acceptable for a fresher)

• Python,N8N,Replit,Cursor,Java : Working knowledge of Python,N8N,Replit,Cursor,Java for data handling, building planning and reconciliation logic, and simple automation.
• Data / spreadsheets: Comfort with spreadsheets, formulas and structured data; willingness to learn Power Query and business intelligence (BI) tools such as Power BI.
• Databases: Basic understanding of databases and the ability to write simple structured query language (SQL) queries.
• Logic & accuracy: Strong attention to detail and a logical, methodical approach to problem-solving.
• Communication: Clear written and spoken communication, able to explain a number or a report simply.

Desirable (a plus, not required — training will be given)

• Automation tools: Exposure to a workflow automation platform (for example, low-code or no-code tools).
• App building: Any experience building small web pages, dashboards or applications.
• ERP / systems: Familiarity with an enterprise resource planning (ERP) system or how factory data is recorded.
• Programming: Basic Java or any second programming language.
• Domain interest: Curiosity about manufacturing, production planning, inventory, costing and operations.

Qualifications

• Bachelor's degree in computer science, information technology, engineering, data, commerce or a related field; or equivalent demonstrated ability.
• Graduates with relevant projects, internships or self-built work (for example, dashboards, small applications or automations) are encouraged to apply.
• Practical evidence of your work — a portfolio, project links or samples — is valued alongside formal qualifications.

What the Role Offers

• Direct mentoring from the Chief Financial Officer (CFO) and senior operations and finance leaders.
• Real ownership of meaningful projects on a live factory floor, not theoretical exercises.
• Broad exposure across finance, operations, inventory, costing and information technology in one role.
• A clear path to grow into a specialist automation, data or systems position as you develop.

Please mention your willingness to travel between the Goregaon office and the Virar factory.

Pay: ₹400,000.00 - ₹700,000.00 per year

Benefits:

• Paid sick time
• Provident Fund

Work Location: In person