The ideal candidate will be responsible for designing, building, and maintaining robust data pipelines to ingest, clean, transform, and integrate diverse public datasets into our knowledge graph.

This role requires a strong understanding of Cloud Platform (GCP) services, data engineering best practices, and a commitment to data quality and scalability.

Qualifications and Skills :

- Education : Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related quantitative field.

- Experience : 6+ years of proven experience as a Data Engineer, with a strong portfolio of successfully implemented data pipelines.

- Programming Languages : Proficiency in Python for data manipulation, scripting, and pipeline development.

- Cloud Platforms and Tools : Expertise in Google Cloud Platform (GCP) services, including Cloud Storage, Cloud SQL, Cloud Run, Dataflow, Pub/Sub, BigQuery, and Apigee. Proficiency with Git-based version control.

Core Competencies :

- Must Have - SQL, Python, BigQuery, (GCP DataFlow / Apache Beam), Google Cloud Storage (GCS)

- Must Have - Proven ability in comprehensive data wrangling, cleaning, and transforming complex datasets from various formats (e.g., API, CSV, XLS, JSON)

- Secondary Skills - SPARQL, Schema.org, Apigee, CI/CD (Cloud Build), GCP, Cloud Data Fusion, Data Modelling

- Solid understanding of data modeling, schema design, and knowledge graph concepts (e.g., Schema.org, RDF, SPARQL, JSON-LD).

- Experience with data validation techniques and tools.

- Familiarity with CI/CD practices and the ability to work in an Agile framework.

- Strong problem-solving skills and keen attention to detail.