Vacancy description
Edgeverve Systems Limited
Pune, भारत
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 https://jobeax.com/link/eg6iTzFmwFrzJtds 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 (ref:hirist.tech)