Infosys - Data Architect
Description
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
Skills
- Analytics
- API
- AWS
- Azure
- Azure Data Factory
- Azure Synapse
- Big Data
- BigQuery
- Cloud
- Data Governance
- Data Ingestion
- Data Lake
- Data Modeling
- Data Quality
- Data Warehousing
- Databricks
- dbt
- Delta Lake
- ELT
- ETL
- GCP
- Hadoop
- Hive
- Lakehouse
- Metadata Management
- MongoDB
- MySQL
- Oracle
- PostgreSQL
- PySpark
- Python
- Redshift
- S3
- Snowflake
- Spark
- SQL
- SQL Server
- SSIS
- Talend
