Position Mission

Own CCI   Prime's data foundation — the BOMs, costing and raw material specifications   the business runs on — deciding what data the Company keeps and what it does   not, pursuing it from operations, supply chain and vendors and entering into   the system, and setting and enforcing the standards that keep it right, so   that purchasing, valuation and cost control improve and a future buyer gets   numbers that survive diligence.

Company and Context

CCI Prime (“the Company” or “CCI”) was founded in 1988 and is co-located in Brooklyn, New York and Bethlehem, PA, the site of a major production expansion and relocation. The Company is a leading domestically-owned manufacturer of frozen and shelf-stable Chinese appetizers — dumplings, bao buns, cured meats, soup dumplings and related items — distributed widely through Asian supermarkets across the United States, with storage facilities in the Western United States enabling bi-coastal distribution. In 2023, Frontenac, a Chicago-based private equity firm, partnered with CCI Prime and President Albert Chan to support growth investments and drive distribution and channel gains across the retail market.

The Company is consolidating production into Bethlehem and closing New York production, and is building toward a sale within the next two to three years. Every role in the finance organization is written to one standard — grow enterprise value and be able to prove it: grow EBITDA and the quality of that EBITDA, release working capital, remove risk from a future diligence process, and leave the Company able to enter a sale process on short notice without a scramble.

Position Summary

This is a new position, created deliberately ahead of any financial systems upgrade rather than after it. The Company's system data — item master, BOMs, routings, standard costs, raw material specifications, vendor and inventory records — is incomplete and inadequate, and the closure of New York production will change BOMs and some SKUs as those items move to Bethlehem. Cleaning and completing that data now, while the change is happening, is far cheaper than migrating bad data into a new system later.

The role is an ownership role, not a reporting one. It sits at two altitudes at once. In the detail, the person in it chases a missing minimum order quantity out of a vendor, corrects a yield on a BOM, and types the specification into the system themselves. At the system level, they decide what data CCI Prime needs and what it does not, write the standards and policies that govern it, and make the case to the rest of the business for why those standards matter. Both halves are the job; neither is optional.

The first priority of the role is the New York to Pennsylvania transition: reviewing and updating every SKU transferring to Bethlehem so that each has a validated BOM, routing and standard cost built and tested before its first production run there. That work is time-boxed by the plant closure and cannot slip. The wider data foundation is built around and through it, not after it.

The role carries real decision authority without carrying headcount. Within the master data domain, this person is the Company's decision maker: what is required, what is optional, what gets retired, who may create or change a record and under what approval. That authority is delegated by the CFO and the VP, Finance and Accounting and is expected to be exercised, not deferred back upward.

The Company is consolidating production into Bethlehem and building toward a sale within the next two to three years. Inventory valuation, standard costing and SKU profitability are among the first things a buyer's quality of earnings review will test. The quality of this person's work is what those answers rest on.

Core Responsibilities

New York Closure and Pennsylvania Transition — First Priority

· This is the first priority of the role. Until every transferring SKU is correctly costed in the system, nothing else on this list matters as much.

· Build, validate and test BOMs, routings and standard costs for every SKU transferring from New York production to Bethlehem, before its first production run in PA.

· Model the cost impact of the transition at SKU level — material, labor, overhead absorption and yield — and flag the products whose economics change materially.

· Support the accounting treatment of the transition: inventory movement, cut-off, write-offs and cost variances.

· Work on-site with the plant, supply chain and production teams at both locations to get the data right at the point it is created.

Own the Data Foundation and Decide What Matters

· Be the Company's decision maker on master data: what data is required, what is optional, what is not worth maintaining, and what should be retired.

· Define and publish the data model for each domain — item and SKU, BOM and routing, standard cost, raw material and packaging specification, vendor, customer and inventory — naming every required field, its definition, its source of truth and its owner.

· Be willing to say no. Data the Company will not keep current is worse than no data, and part of this role is deciding what to stop collecting.

· Establish one source of truth per data element and eliminate the competing spreadsheets that compete with it.

· Identify and eliminate duplicate, orphaned, obsolete and incorrect records, and build the validation and exception rules that prevent them recurring.

Own BOMs and Costing

· Own every bill of material in the business: structure, components, quantities, yields and scrap, units of measure, and the routings attached to them.

· Own standard costing — the cost roll, its cadence, the inputs behind it and the variance analysis that follows it — and keep standards reflecting what production actually costs.

· Operate change control over BOMs: no BOM revision without a documented reason, a cost impact and an approval, and no SKU enters production without a costed, approved BOM.

· Quantify the cost impact of formulation, vendor, pack size and process changes before they are approved, and take that analysis to the VP, Finance and Accounting and to Supply Chain.

· Support the accounting treatment of costing: PPV and absorption variances, revaluation, reserves and obsolescence.

Manage Specifications for Raw Materials, Packaging and BOMs

· Build and own the specification library for every raw material, ingredient and packaging item the Company buys.

· Maintain the full specification record: minimum order quantity, order multiples, pack and case configuration, unit of measure and the conversions between them, lead time, price and price breaks, vendor item number, country of origin, shelf life, storage requirements and allergen attributes.

· Keep specifications current as vendors, formulations and pack sizes change, rather than allowing the library to decay after the initial build.

· Make specifications usable by the people who need them — purchasing, planning, production, FSQA and accounting — in a form each can act on.

Chase the Information — Operations, Supply Chain and Vendors

· Pursue missing and unverified data to closure with operations, supply chain, planning, FSQA and vendors directly. This is a core, ongoing duty of the role, not a start-up task.

· Maintain a visible open-items list — what is missing, who owns the answer, when it was requested and when it is due — and work it weekly.

· Escalate promptly to the VP, Finance and Accounting when a request goes unanswered, rather than absorbing the gap quietly.

· Enter and validate the information in the system personally where that is the fastest route to accuracy.

· Build the habit, across the business, of the data arriving without being chased.

Govern the System, Set Policy and Bring the Business With You

· Write the master data policies and standards, take them through approval, and enforce them.

· Define who may create or change each type of record, the approval path for each, and the consequences of working around it.

· Communicate the standards to all affected staff and explain why they matter — what a wrong BOM does to a margin, what a missing MOQ does to a purchase order, what a bad standard cost does to the financial statements.

· Train new and existing staff who touch master data, in the languages the workforce uses where needed.

· Audit compliance on a regular cadence and report the results to the VP, Finance and Accounting.

· Own the improvement of the system over time, including requirements for any future financial software upgrade or replacement.

Project Prioritization and Sequencing

· Work closely with Project Management to sequence and prioritize this role's workstreams — the New York to Pennsylvania transition first, then master data remediation, specification build, costing and reporting — against everything else the Company has in flight.

· Represent every data, costing and system workstream on the Company project plan with an agreed priority, owner and date, rather than running a private list.

· Hold a standing cadence with the Project Manager to re-sequence as the transition plan moves, and flag early where a data dependency will hold up another project.

· Resolve competing requests from operations, supply chain, purchasing and accounting through that forum rather than by whoever asks most insistently; escalate to the CFO where priorities genuinely conflict.

· Report progress in a form the project office can use, and be honest about slippage while it can still be recovered.

Inventory, Purchasing and Valuation Support

· Reconcile inventory on-hand, location, lot and valuation data to physical and cycle counts, and drive accuracy to a sustained standard.

· Build and run exception reporting for negative inventory, stale lots, Received Not Invoiced aging, costing errors and unexplained variances.

· Provide purchasing with reliable price variance, vendor spend, MOQ, lead time and concentration analysis to support sourcing and negotiation.

Reporting, Analytics and Automation

· Replace manual spreadsheet reporting with automated dashboards and scheduled reports drawn from a single source of truth.

· Build and maintain reporting on sales and margin by customer, channel and SKU, volume/price/mix bridges, inventory and working capital KPIs, and cost performance.

· Use scripting, automation and AI tooling to eliminate repetitive data preparation work, and document the hours saved.

· Respond to ad hoc analytical requests from the CFO, VP Finance and Accounting and the executive team with fast, accurate, well-sourced answers.

Controls, Documentation and Diligence Readiness

· Document data definitions, lineage and calculation logic for the metrics the Company reports and a buyer will test, so that any figure can be traced to source.

· Rebuild and validate at least twenty-four months of history for the key profitability and inventory metrics.

· Build the detective reporting that makes controls work in practice — exception reports, tolerance checks and reconciliation dashboards.

· Leave behind written procedures that survive turnover and satisfy diligence.

Qualifications and Key Selection Criteria

· Bachelor's degree in accounting, finance, supply chain, information systems, data analytics, industrial engineering, food science or a related field.

· Three or more years of analytical or master data experience in a manufacturing environment; food manufacturing strongly preferred.

· Direct, hands-on ownership of BOMs and standard costing in a manufacturing ERP — Sage X3 preferred, SAP, NetSuite, Oracle or comparable — including cost rolls and BOM change control.

· Experience building and maintaining raw material and packaging specifications, including MOQ, order multiples, units of measure and conversions, lead times and price breaks.

· Demonstrated experience defining data standards or governance for an organization, and enforcing them across departments the person did not manage.

· Working understanding of manufacturing cost: yields and scrap, standard cost rolls, purchase price variance and overhead absorption.

· Demonstrated persistence obtaining information from internal teams and external vendors, with an example of a stalled data problem driven to closure.

· SQL and the ability to extract and join data directly from source systems.

· Advanced Excel including Power Query; experience building dashboards in Power BI, Tableau or a comparable tool.

· Demonstrated experience cleaning and remediating bad data at scale, and designing the controls to keep it clean.

· Comfort with scripting (Python or similar) and with AI tooling for data work is a strong plus.

· Exceptional accuracy, documentation discipline and personal organization.

· Willing and able to work on the plant floor at both sites, and effective in a multi-lingual environment.