Data Architect

The Data Architect is responsible for designing, governing, and optimizing an organization's data architecture with a primary focus on treating data as a strategic asset. This role ensures that data is accurate, accessible, secure, interoperable, and aligned with business goals. The Data Architect works across business, technology, and analytics teams to create data models / data product, standards, and architectures that empower advanced analytics, AI, automation, and digital transformation.

1. Data Strategy and Architecture Design:Developing and optimizing database models and overall data architecture to store and retrieve company information efficiently. This includes creating blueprints for developing, testing, and maintaining databases.
2. Translating Business Requirements:Collaborating with business leaders and teams to translate information requirements into data-centric solutions, including databases, data warehouses, and data streams.
3. Data Modelling and Management:Designing conceptual and logical data models and flowcharts, defining database structures, and creating procedures to ensure data accuracy and accessibility.
4. Ensuring Data Quality, Integrity, and Security:Focusing on improving data quality, accessibility, and security across all systems and platforms. This involves defining security and backup procedures and ensuring compliance with data regulations like GDPR and data governance guidelines.
5. System Implementation and Optimization:Installing and configuring information systems, migrating data from legacy systems to new solutions, and improving system performance through testing, troubleshooting, and integrating new elements.
6. Collaboration and Coordination:Working closely with product mangers, product owners, software developers, and other IT teams to implement data-related solutions and realize end-to-end data strategies.
7. Technology Evaluation:Evaluating and recommending new technologies to enhance data management and supporting data analytics, AI solutions, and business intelligence projects with a well-designed data landscape.

8. Adherence to Standards:Ensuring that industry-accepted data architecture principles and standards are integrated and followed for modelling, stored procedures, replication, regulations, and security.

Required

Bachelor's degree in Computer Science, Information Systems, Data Management, or related field.

8-12 years of experience in data architecture, data engineering, or database development.

Expertise in database technologies (SQL, NoSQL), data mining, and programming languages like Python, Scala, Java.

Proficiency in data modelling (Canonical Data Model, Semantic Data Model) and schema design.

Familiarity with ETL (Extract, Transform, Load) tools and processes for efficiently transforming and loading data.

Hands-on experience with cloud data platforms (GCP/Azure/AWS) and modern data processing tools.

Solid understanding of data governance, data quality, metadata management and master data management(MDM), referenced data management, transactions data management.

Experience with data lakehouse architectures, data mesh, or data fabric.

Familiarity with structural and non structural like big data tools (Hadoop/Spark, Kafka, Databricks, Big Query).

Experience supporting AI/ML workloads with high-quality data structures.

Strong analytical and problem-solving abilities.

Excellent communication and stakeholder management skills.

Ability to create clear architecture artifacts and documentation.

Adaptability and a commitment to continuous learning to stay updated with evolving technologies.

Good To have

Master's degree or relevant certifications (GCP Data Engineer/Azure/AWS Data Architect, TOGAF).

Exposure to GCP data service like (Postgres, Big Query etc.)

Exposure in Automative Industry.