Overview
Skills
Job Details
Architectural Design: Define and implement enterprise data architecture strategies, including data warehousing, data lakes, and real-time data systems.
Data Modeling: Develop and maintain logical, physical, and conceptual data models to support analytics, reporting, and operational systems.
Platform Management: Select and oversee implementation of cloud and on-premises data platforms (e.g., Snowflake, Redshift, BigQuery, Azure Synapse, Databricks).
Integration & ETL: Design robust ETL/ELT pipelines and data integration frameworks using tools such as Apache Airflow, Informatica, dbt, or native cloud services.
Data Governance: Collaborate with stakeholders to implement data quality, data lineage, metadata management, and security best practices.
Collaboration: Work closely with data engineers, analysts, software developers, and business teams to ensure seamless and secure data access.
Performance Optimization: Tune databases, queries, and storage strategies for performance, scalability, and cost-efficiency.
Documentation: Maintain comprehensive documentation for data structures, standards, and architectural decisions.
Deep understanding of modern data architecture, including Lakehouse, Medallion architecture, and Data Mesh.