Position Title:
Data Analyst – ERP & Master Data
Reports To:
Director of Data & Business Analytics
Location:
Chagrin Falls, OH / Hybrid (APPLICANTS MUST BE WITHIN COMMUTING DISTANCE)
Company Overview
TransTech provides custom-engineered and fabricated solutions for liquids and gas processing, storage, TransTech is a leading provider of specialized infrastructure and custom-engineered equipment for diverse industries. Our expansive capacity and technical expertise enable large-scale production of complex, high-quality equipment while meeting rigorous quality and safety standards. TransTech’s companies provide comprehensive solutions for gas and liquid processing, storage, transfer, and utilization, adhering to ASME, API, and TEMA standards to ensure reliability and precision in every project. From individual services to full project solutions, TransTech’s teams deliver expert engineering, fabrication, construction, operations and maintenance, supporting projects nationally and internationally. We help customers achieve impactful, sustainable results with a commitment to safety, community, and environmental responsibility. Job Summary This role reports to the Director of Data & Business Analytics as a key member of the TransTech Data & Analytics team, working directly with Finance, Operations, Supply Chain and IT leadership across all business units and with our ERP implementation partners. TransTech is consolidating the separate ERP systems of its business units onto a single enterprise platform (IFS Cloud), and data readiness is the single largest determinant of whether that program succeeds. The Data Analyst will be the hands-on data lead for the implementation: owning the extraction, profiling, cleansing, mapping, transformation, mock loading and reconciliation of legacy master and transactional data into IFS, and driving business owners to sign off on data they will live with for the next decade. Following go-live, the role becomes the permanent owner of enterprise master data governance (Item, Customer, Vendor and related domains) and of the data engineering pipelines that bring ERP data into TransTech’s Microsoft Fabric platform and Power BI reporting. The intended growth path is from ERP data lead into a Senior or Lead Data Engineer or Data Architect role within Data & Analytics, with leadership opportunities also open in ERP and Business Systems, Finance, or Operations. The ideal candidate has been through at least one full ERP implementation as the person responsible for the data, understands manufacturing and fabrication data end to end (items, BOMs, routings, customers, vendors, inventory, open orders, GL), and combines rigorous attention to detail with the credibility to challenge business owners and the pragmatism to get to a decision. They are equally at home in a modern data engineering toolset: repeatable pipelines and notebooks, Git, an agile backlog, and AI assistants used to move faster without compromising accuracy.
Essential Duties and Responsibilities
ERP Data Migration & Readiness:
- Serve as TransTech’s data lead for the ERP implementation, owning the data workstream plan, deliverables and readiness gates with the implementation partner and program management.
- Extract and profile master and transactional data from legacy systems (SYSPRO, Syteline/CloudSuite Industrial and others), quantifying volumes, completeness, duplication and quality issues by domain.
- Build and maintain source-to-target mapping and transformation specifications for each data object (Item/Part, BOM, Routing, Customer, Vendor, Chart of Accounts, Inventory, Open AR/AP, Open Sales and Purchase Orders, Fixed Assets, Employees) against the IFS Cloud data model and load templates.
- Design and execute cleansing, de-duplication, standardization and enrichment routines in SQL, Python and Fabric notebooks; track defects to closure with business data owners.
- Prepare and execute mock loads, cutover rehearsals and the production cutover; reconcile counts, quantities and financial values to source; run business validation and sign-off; and maintain the data issue log, decision log and cutover checklist.
- Support data-related integration requirements between IFS Cloud and surrounding systems (OneStream, Salesforce, Procore, Smartsheet, Fabric).
Master Data Governance:
- Lead harmonization of Item, Customer and Vendor master data across business units (numbering and naming standards, required attributes, hierarchies, cross-references) and facilitate the cross-BU decisions needed to converge on one standard.
- Establish and operate the post-go-live governance model: data ownership and stewardship roles, create/change/retire workflows, approval controls and standards documentation.
- Define, measure and publish data quality KPIs by domain and business unit, drive remediation, and act as the enterprise escalation point for master data questions.
Data Engineering & Analytics:
- Design, build and operate the pipelines that land source-system data in Microsoft Fabric (mirroring, Data Factory pipelines, Dataflows, PySpark/SQL notebooks) across Bronze, Silver and Gold layers, including incremental loads, orchestration, monitoring and automated data quality checks.
- Build the ERP extracts and Silver/Gold models that replace legacy business-unit reporting after go-live, ensuring continuity of executive and operational Power BI reporting through cutover, and validate that reported figures reconcile to the ERP.
- Automate recurring data preparation, validation and reconciliation with SQL, Python/PySpark and Power Query, replacing manual and spreadsheet-based processes with tested, scheduled code.
- Apply software engineering practices to data work: Git-based version control in Azure DevOps, pull requests and code review, dev/test/prod promotion, and documentation as code.
Ways of Working, Training & Documentation:
- Work within the team’s agile delivery model (user stories, sprint planning, backlog refinement, reviews and retrospectives in Azure DevOps), breaking migration and governance work into estimable, demonstrable increments.
- Use AI tools (Microsoft Copilot, ChatGPT, Claude, AI-assisted coding) as a routine part of profiling, code generation, documentation and analysis, with sound judgment about validating outputs before they are relied on.
- Develop and maintain data standards, data dictionaries, mapping documents, runbooks and end-user guides; train and coach business data owners, stewards and analysts; and mentor other members of the Data & Analytics team.
Education and/or Experience:
- Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Accounting/Finance, Supply Chain or a related field (or equivalent experience).
- Five or more years of progressive data analysis, data management or business systems experience in a manufacturing, fabrication, engineered-equipment or industrial services environment.
- Hands-on ownership of the data workstream on at least one full-lifecycle ERP implementation or migration, including extraction, cleansing, mapping, mock loads, reconciliation and cutover (required).
- Strong working knowledge of ERP data structures across manufacturing, supply chain and finance: item/part master, BOMs and routings, customer ship-to/bill-to structures, vendors, inventory and lot/serial data, open orders and GL/sub-ledger balances.
- Advanced SQL and Excel required; Python/PySpark and Power Query strongly preferred.
- Hands-on experience building data pipelines and lakehouse or warehouse models on Microsoft Fabric, Azure Synapse, Databricks or a comparable platform; medallion architecture and Power BI familiarity preferred.
- IFS Cloud experience strongly preferred; SYSPRO, Infor Syteline/CloudSuite Industrial, or Infor Visual experience also relevant.
- Master data management or data governance experience, and experience consolidating multiple entities, sites or acquired businesses onto a common platform, preferred.
- Working knowledge of Git and Azure DevOps (or GitHub/Jira), experience on an agile/scrum team, and demonstrated use of AI assistants in day-to-day analytical and engineering work, preferred.
Personal Attributes:
- Highest level of integrity and ethics.
- Exceptional attention to detail; Strong use of validation to source systems is a must.
- Comfortable owning outcomes in an ambiguous, fast-moving program environment with firm deadlines.
- Forges strong cross-functional partnerships and drives business owners to timely decisions.
- Explains complex data concepts, trade-offs and results clearly to non-technical managers and executives.
- Engineering mindset and continuous improvement orientation: prefers repeatable, tested, version-controlled solutions over one-off fixes.
- Curious, self-directed learner who adopts new tools quickly, including generative AI, and shares what works with the team.
- Works independently with minimal supervision, leads others through change, and interacts effectively at all levels of the organization with a service attitude.
Benefits Designed to Work for You:
- Free HSA health plan or traditional PPO
- 401(k) with generous company match (Safe Harbor)
- Dental, vision, and optional coverage like accident & critical illness insurance
- HSA and FSA accounts to save on healthcare costs
- Company-paid Life, Long Term Disability, and AD&D insurance
- Confidential support for mental health, family matters, legal concerns, and more through our Employee Assistance Program
- Discounts on gyms, shopping & entertainment
- Health benefits kick in fast – first of the month after 30 days
Time Off We offer a variety of paid time off options to support rest, wellness, and personal needs:
- Paid Time Off
- Paid Holidays
- Bereavement Leave
This organization provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. #TTE
