Reference Data Sr. Associate Engineer

• 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.

Functional Skills:

Must-Have Skills:

• Knowledge of controlled vocabularies, classification, ontology and taxonomy

• Experience in ontology development using Semaphore, or a similar tool

• Hands on experience writing SPARQL queries on graph data

• Excellent problem-solving skills and the ability to work with large, complex datasets

• 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

• 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.