Job Description :

- Define and own enterprise data architecture, standards, principles, and technology strategies aligned with business objectives.

- Design scalable, secure, and high-performance data architectures across structured, semi-structured, and unstructured data environments.

- Develop conceptual, logical, and physical data models to support enterprise applications, analytics, reporting, and data products.

- Define data ingestion, integration, transformation, storage, and consumption patterns across the organization.

- Design modern data platforms including data lakes, data warehouses, lakehouses, and cloud-based data ecosystems.

- Work with engineering, analytics, product, security, and business teams to understand data requirements and translate them into architectural solutions.

- Define architecture for batch and real-time data processing and streaming use cases.

- Establish data governance, data quality, metadata management, lineage, security, privacy, and access-control frameworks.

- Evaluate and recommend appropriate databases, data platforms, integration technologies, and cloud services.

- Design APIs and data integration patterns for seamless data exchange across applications and platforms.

- Ensure data architecture supports scalability, reliability, performance, availability, and cost optimization.

- Review existing data landscapes and identify opportunities for modernization, consolidation, migration, and optimization.

- Create architecture diagrams, technical standards, reference architectures, and detailed design documentation.

- Provide technical guidance to data engineers, developers, BI teams, and other technology teams.

- Ensure compliance with enterprise security policies, regulatory requirements, and data protection standards.

- Collaborate with stakeholders to establish data strategies and roadmaps for future-state architecture.

Technical Skills :

- Data Architecture: Enterprise Data Architecture, Data Modelling, Data Integration, Data Warehousing, Data Lakes, Lakehouse Architecture

- Databases: Oracle, SQL Server, PostgreSQL, MySQL, MongoDB

- Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform

- Cloud Data Services: AWS S3, Redshift, Glue, Azure Data Lake, Azure Synapse, Data Factory, Google BigQuery

- Modern Data Platforms: Snowflake, Databricks, Delta Lake

- Big Data Technologies: Apache Spark, Hadoop, Hive

- Programming & Query Languages: SQL, Python, PySpark

- ETL / ELT: Informatica, Talend, DataStage, SSIS, dbt