Roles & Responsibilities:
- Work with Reference Data Product Owner, external resources and other engineers as part of the product team
- Develop and maintain semantically appropriate concepts
- Identify and address conceptual gaps in both content and taxonomy
- Maintain ontology source vocabularies for new or edited codes
- Support product teams to help them leverage taxonomic solutions
- Analyze the data from public/internal datasets.
- Develop a Data Model/schema for taxonomy.
- Create a taxonomy in Semaphore Ontology Editor.
- Perform Bulk-import data templates into Semaphore to add/update terms in taxonomies.
- Prepare SPARQL queries to generate adhoc reports.
- Perform Gap Analysis on current and updated data
- Maintain taxonomies in Semaphore through Change Management process.
- Develop and optimize automated data ingestion / pipelines through Python/PySpark when APIs are available
- Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
- Identify and resolve complex data-related challenges
- Participate in sprint planning meetings and provide estimations on technical implementation.
Basic Qualifications and Experience:
- Any degree with 5 - 9 years of experience in Business, Engineering, IT or related field
Functional Skills:
Must-Have Skills:
- Knowledge of controlled vocabularies, classification, ontology and taxonomy
- Experience in ontology development usingProgressSemaphore, or a similar tool like Pool Party etc
- Hands on experience writingSPARQL queries on graph data
- Excellent problem-solving skills and the ability to work with large, complex datasets
- Strong understanding of data modeling, data warehousing, and data integration concepts
Good-to-Have Skills:
- Hands on experience writing SQL using any RDBMS (Redshift, Postgres, MySQL, Teradata, Oracle, etc. ).
- Experience using cloud services such as AWS or Azure or GCP
- Experience working in Product Teams environment
- Knowledge of Python/R, Databricks, cloud data platforms
- Knowledge of NLP (Natural Language Processing) and AI (Artificial Intelligence) for extracting and standardizing controlled vocabularies.
- Strong understanding of data governance frameworks, tools, and best practices
Professional Certifications:
- Databricks Certificate preferred , Progress Semaphore
- SAFe Practitioner Certificate preferred
- Any Data Analysis certification (SQL, Python)
- Any cloud certification (AWS or AZURE)
Soft Skills:
- Strong analytical abilities to assess and improve master data processes and solutions.
- Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders.
- Effective problem-solving skills to address data-related issues and implement scalable solutions.
- Ability to work effectively with global, virtual teams
