Mandatory Skills Description:

Education: Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent professional experience). An advanced degree is a plus but not required.

Experience: Approximately 3-5 years of experience in data architecture, data engineering, or a related data management role. A proven track record in designing data solutions and managing data schemas is expected.

Data Modelling & Databases: Strong proficiency in data modelling and database design. You should be comfortable creating ER diagrams and defining relational schema, as well as working with NoSQL databases (e.g. document or graph databases). Practical experience with SQL and at least one relational database is required, as well as deep knowledge of other data store types (especially graph databases) is highly needed.

Data Pipeline Development: Hands-on experience developing data pipelines and integration workflows. This includes proficiency in ETL/ELT tools or frameworks (or custom scripting with Python/SQL) to gather and transform data. You should understand how to optimise data flow and have experience with batch processing; experience with real-time streaming data (e.g. using Kafka or equivalent) is a plus.

Ontologies & Knowledge Graphs: Exposure to semantic data modelling, ontologies, or knowledge graph construction. Experience in structuring data with ontologies (e.g. using RDF/OWL standards)



or implementing a knowledge graph to link datasets can be very beneficial, since it helps in creating a unified data vocabulary and enriches the context for AI models.

Cloud Data Platforms: Experience working with cloud-based data platforms or big data technologies. While our approach is cloud-agnostic, you should be familiar with concepts like data lakes, data warehouses, and distributed computing in a cloud environment (e.g. using AWS, Azure, or GCP services). The ability to design solutions that leverage cloud scalability and tools for storage and processing is important.

Data Governance & Security: Solid understanding of data governance principles and best practices. You should be knowledgeable about data privacy regulations and data protection techniques, ensuring compliance in how data is stored and used. Experience implementing data quality checks, defining data standards, and using or setting up metadata management tools will be helpful.

Communication & Teamwork: Excellent communication skills with the ability to collaborate in cross-functional teams. You should be able to translate complex data architecture concepts into clear terms for project managers or stakeholders, and work closely with engineering teams to guide implementation. Problem-solving aptitude and a willingness to mentor junior data team members are also important in our collaborative environment.

📌 Data Architect (Noida)
🏢 Luxoft
📍 Noida