Staff Specialist, EHSS Data
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- Pay
- Pay not listed
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- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and maintain EHSS data models, source-to-target mappings, and transformation logic
Define data-quality controls, validation rules, and reconciliation processes
Translate approved business definitions into reusable, analytics-ready datasets
Validate data and perform root-cause analysis across sources, mappings and products
Maintain technical metadata, data dictionaries, and transformation specifications
From the employer’s posting
Design and maintain EHSS data models, source-to-target mappings, transformation logic, and technical data specifications.
Define and maintain data-quality controls, validation rules, reconciliation processes, and technical acceptance criteria.
Translate approved business definitions and rules into reusable, analytics-ready data structures and datasets.
Perform data validation, reconciliation, and root-cause analysis across source systems, mappings, transformations, and data products.
Maintain technical metadata, mapping documentation, data dictionaries, and transformation specifications.
Education & alternatives
Requirements * Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, Engineering, or a related technical discipline. * 6-10+ years of experience in data engineering, data modelling, data integration, business intelligence engineering, or related technical data roles. * Advanced proficiency in SQL and relational database concepts. * Experience designing data models, source-to-target mappings, transformation logic, and technical data specifications. * Experience with data profiling, data-quality controls, reconciliation, validation, and structured testing. * Experience translating complex business requirements into precise, testable technical specifications. * Experience working with enterprise databases, cloud-based data environments, or data platforms. * Strong analytical and problem-solving skills, including investigation of complex data defects across systems, mappings, and data pipelines. * Strong communication skills and the ability to explain technical data concepts to non-technical stakeholders. Preferred Qualifications
Tools in this posting
- Python
- SQL
- Azure
- GCP
- Snowflake
- SQL Server
Source — Tool mentions in context
Data Engineering & Platforms * Experience with Snowflake, SQL Server, Google Cloud Platform (GCP), Azure Data Services, or comparable enterprise data platforms. * Working proficiency in SQL and Python for data transformation, validation, automation, or data engineering activities. * Experience with Git, Azure DevOps, or similar version-control and development-management tools. * Experience with metadata, data-quality, data-catalogue, lineage, or data-governance capabilities. Enterprise Data & Digital Enablement
Requirements * Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, Engineering, or a related technical discipline. * 6-10+ years of experience in data engineering, data modelling, data integration, business intelligence engineering, or related technical data roles. * Advanced proficiency in SQL and relational database concepts. * Experience designing data models, source-to-target mappings, transformation logic, and technical data specifications. * Experience with data profiling, data-quality controls, reconciliation, validation, and structured testing. * Experience translating complex business requirements into precise, testable technical specifications. * Experience working with enterprise databases, cloud-based data environments, or data platforms. * Strong analytical and problem-solving skills, including investigation of complex data defects across systems, mappings, and data pipelines. * Strong communication skills and the ability to explain technical data concepts to non-technical stakeholders. Preferred Qualifications
Enterprise Data & Digital Enablement * Experience validating production data products, data pipelines, or enterprise data solutions. * Familiarity with SAP, ServiceNow, or other enterprise business-system data structures. * Understanding of how trusted data supports reporting, analytics, automation, AI-enabled solutions, and intelligent business processes. * Experience modernizing legacy databases, SQL logic, or manually managed data processes. Domain & Professional Experience
Domain & Professional Experience * Experience supporting EHSS, Quality, Manufacturing, Supply Chain, or other regulated operational functions. * Familiarity with EHSS processes, management systems, sustainability reporting, or regulatory requirements. * Experience working in a global, cross-functional organization. * Relevant certifications in data engineering, Snowflake, SQL, Azure, GCP, or comparable data technologies Job Profile(s):
Posting record
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- Live
- First seen by us
- Oct 3, 2026 · 27 days ago
- Recorded sightings
- 129
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Sep 16, 2026
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