Data Architect

• Develop architectural strategies for data modelling, design and implementation to meet stated requirements for metadata management, master data management, Data warehouses, ETL and ELT.
• Analyzing business requirements, designing scalable/ robust data models, documenting conceptual, logical physical data model design, helping developers in development/ creating DB structures and supporting developers throughout the project life cycle.
• Lead and Mentor Data Engineers: This role will be responsible for leading and developing a team of data engineers focused on the growth in the teams skills and ability to execute as a team using DevOps and Data Ops principles.
• Investigate new technologies, data modelling methods and information management systems to determine which ones should be incorporated onto data architectures, and develop implementation timelines and milestones.
• Recognizes and resolves conflicts between models, ensuring that information and data models are consistent with the ecosystem model (e.g., entity names, relationships and definitions).
• Participates in the design of the information architecture: supports projects, reviews information elements including models, glossary, flows, data usage.
• Provides guidance to the team in achieving the project goals/milestones.
• Works independently within broad guidelines and policies, with guidance in only the most complex situations.
• Contribute as an expert to multiple delivery teams, defining best practices, building reusable design components, capability building, aligning industry trends and actively engaging with wider data communities.

Skills and Experience

• Graduate or post graduate in Computer science/Electronics/Software engineering.
• 6+ years of relevant experience in Data modelling for DW analytics applications (OLAP) / Database related technologies.
• Expert data modelling skills (i.e. conceptual, logical and physical model design, experience with Enterprise Data Warehouses and Data Marts).
• Solid understanding of cloud database technologies and services (eg..GCP, Redshift, Aurora, DynamoDB, etc)
• Experience in working with data governance, data quality, and data security teams.
• Experienced in knowledge-driven data processing techniques like data curation, representation, standardization, normalization and any other type of processing that prepares the data for integration, persistence, analysis, exchange/share and so forth.
• Experience in handling very large DBs and large data volumes
• Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement and upcoming data ingestion and integration technologies such as stream data integration and data virtualization.
• Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
• Knowledge with popular data discovery, analytics, and BI software tools like MicroStrategy, Tableau, Power BI and others for semantic-layer-based data discovery.
• Ability to lead and mentor teams for effective delivery
• Crisp and effective executive communication skills, including significant experience presenting cross-functionally and across all levels.