Forward Deployed Data Engineer

CoorsTek; Village of Potsdam (NY); On-site; USD 115,000 - 155,000; Full time

Benefits offered by this job

Paid Time Off

Medical, Dental, Vision Benefits

Company-Matched 401K

Performance-Based Bonuses

Mentorship Program

Job summary

CoorsTek is seeking a Forward Deployed Data Engineer in Potsdam, NY. This role involves collaborating with manufacturing sites to transform data needs into Databricks products and analytics solutions. Ideal candidates will have over 5 years of data engineering experience and a bachelor’s degree.

The position offers a competitive salary range of USD 115,000 – USD 155,000 based on experience and qualifications, along with comprehensive benefits such as medical, dental, wellness reimbursements, and paid time off.

Qualifications

• 5+ years of experience in data engineering or related fields.
• Experience working with manufacturing or plant operations.
• Ability to write SQL and Python-based transformation logic.

Responsibilities

• Understand workflows and data needs while embedding with manufacturing sites.
• Develop and support Databricks-based data products and pipelines.
• Document lineage, transformation logic, and reusable patterns.

Skills

Data modeling

SQL

Python

Data governance

Manufacturing performance concepts

Education

Bachelor’s degree in Engineering or related field

Tools

Databricks

Azure

Job description

A Forward Deployed Data Engineer works to understand workflows, data sources, and decision needs, translating them into governed Databricks data products, reusable data models, analytics, and AI‑enabled solutions.

Responsibilities

• Understand workflows, constraints, decision points, and data needs while embedding with manufacturing sites, business units, and functional teams.
• Identify high‑value opportunities for data, analytics, AI, or workflow enablement by partnering with plant leaders, engineers, quality, supply chain, maintenance, finance, and business leaders.
• Assess manufacturing data alignment across SAP, QAD, Apriso, Ignition, InfinityQS, LIMS, CMMS, equipment data, spreadsheets, databases, and other sources at a plant‑by‑plant level.
• Translate ambiguous business and manufacturing problems into practical data requirements, data products, analytics, applications, and implementation plans.
• Define mappings, data definitions, transformation rules, business logic, data quality rules, and metric calculations for trusted manufacturing insights.
• Help establish an aligned manufacturing data hierarchy across sites, equipment, work centers, operations, products, materials, orders, quality events, and maintenance events.
• Develop and/or support Databricks‑based data products, pipelines, notebooks, dashboards, models, and applications using approved architecture and governance patterns.
• Partner with IT Data & Analytics on ETL/ELT patterns using Databricks, Delta Lake, Unity Catalog, workflows, governed tables, semantic definitions, and reusable data assets.
• Balance local plant flexibility with enterprise standardization by defining what should be harmonized centrally and what plant variation should be preserved.
• Improve data capture, completeness, quality, and ownership where source data is inconsistent, manual, incomplete, or not decision‑ready.
• Create minimum viable data products with real users, then mature successful solutions into governed, supportable production patterns, including Databricks‑hosted applications.
• Partner with IT architecture, cybersecurity, enterprise applications, integration, infrastructure, and manufacturing IT/OT to meet standards for identity, access, lineage, logging, supportability, resiliency, and responsible AI usage.
• Document lineage, transformation logic, business definitions, solution designs, runbooks, ownership models, and reusable patterns that can scale across plants and business units.
• Coach plant engineers, analysts, and business users on data definitions, data quality, Databricks workflows, analytics adoption, and responsible AI‑enabled capabilities.
• Serve as a point of contact for the feedback loop between the business and IT by identifying recurring plant needs, architecture gaps, and reusable platform improvements.

Education

Bachelor’s degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required. Master’s degree preferred.

Experience

5+years of progressive experience in data engineering, analytics engineering, manufacturing systems, industrial technology, enterprise analytics, operational excellence, or a related field. 3+years working with manufacturing, plant operations, quality, supply chain, maintenance, engineering, or industrial data environments preferred. Experience translating operational workflows into practical data, analytics, dashboard, pipeline, or application solutions.

Functional & Technical Knowledge, Skills & Abilities

• Strong ability to bridge plant operations, business leadership, and IT by translating manufacturing problems into data, analytics, application, and architecture requirements.
• Strong understanding of manufacturing performance concepts such as yield, scrap, rework, throughput, cycle time, downtime, quality events, maintenance events, OEE, inventory, and production scheduling.
• Strong working knowledge of data modeling, transformation, quality, semantic layers, metric definitions, metadata, lineage, and data governance.
• Working knowledge of Databricks capabilities – Delta tables, notebooks, workflows/jobs, SQL, Unity Catalog, data lineage, and governed analytical access patterns.
• Ability to write and review SQL and Python‑based data transformation logic; PySpark experience preferred.
• Ability to define practical data hierarchies and translation layers that support local operational needs while enabling enterprise reporting and leadership insight.
• Ability to develop prototypes, MVPs, dashboards, data products, and Databricks‑enabled applications that validate value quickly and improve iteratively.
• Ability to partner effectively with IT teams on architecture, cybersecurity, integration, enterprise applications, infrastructure, support, and lifecycle expectations.
• Strong communication and documentation skills, including data dictionaries, mapping documents, process flows, business logic definitions, architecture notes, testing evidence, and runbooks.
• Ability to manage multiple initiatives, prioritize by business value, work in ambiguity, and travel frequently for plant‑facing data alignment and enablement.

Preferred Certifications

• Relevant Databricks certifications – Data Engineer, Data Analyst, Machine Learning, or Lakehouse Fundamentals.
• Relevant Microsoft Azure, Power BI, data engineering, analytics, AI, or cloud certifications.
• Lean Six Sigma, operational excellence, manufacturing systems, ISA‑95, APICS, or related industrial operations certifications.

Salary

Target hiring range: USD 115,000.00 – USD 155,000.00. Actual compensation is commensurate with experience, skills, and education.

EEO Statement

CoorsTek strives to give all qualified applicants equal opportunity and to make selection decisions on job related factors. Do not provide any information on the application which will indicate your race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity, pregnancy, genetic information, veteran status, or any other status protected by law or regulation.

Benefits

• Paid Time Off
• Medical, Dental, Vision Benefits
• Company‑Matched 401K (USA only)
• Company‑Matched Pension Plan (CANADA only)
• HSA (Health Savings Account) with Company Contribution
• Wellness Reimbursement Program (USA only)
• Voluntary Benefits (Pet Insurance, Legal Insurance, Accident Insurance, Critical Illness Insurance & more) (USA only)
• Safety Programs (reimbursement for safety shoes and company provided safety glasses)
• Performance‑Based Bonuses for all Employees
• Employee Recognition Programs
• Mentorship Program
• Community & Volunteer Events & MORE!