Data Architect

Azure Expertise: The architect should have experience in architecting large scale analytics solutions using native services such as Azure Synapse, Data Lake, Data Factory, HDInsight, Databricks, Azure Cognitive Services, Azure ML, Azure Event Hub.

Assist with creation of a robust, sustainable architecture that supports requirements and provides for expansion with secured access

Experience in building/ running large data environment for BFSI clients

Work with customers, end users, technical architects, and application designers to define the data requirements and data structure for BI/Analytic/ solutions

Designs conceptual and logical models for the data lake, data warehouse, data mart, and semantic layer (data structure, storage, and integration). Lead the database analysis, design, and build effort

Communicates physical database designs to lead data architect / database administrator

Evolves data models to meet new and changing business requirements

Work with business analysts to identify and understand requirements and source data systems

Expert in big data technologies on Azure/GCP

Experience with ETL platform like ADF / Glue / Ab Initio/ Informatica / Talend / Airflow

Experience in data visualization tools like Tableau, Power BI etc.

Experience in a data engineering, metadata management, database modelling and development role

Strong experience in handling streaming data with kafka

Understanding of Data APIs, Web services

Experience in Data security and Data Archiving/Backup, Encryption and define the standard processes for same.

Experience in setting up DataOps and MLOps

Ensure that the database designs fulfil the requirements, including data volume, frequency, and long-term BI/Analytics growth requirements

Work with other architects to ensure that all components work together to meet objectives and performance goals as defined in the requirements.

Improve system performance by conducting tests, troubleshooting, and integrating new elements

Coordinate with the Data Science Teams to identify future data needs and requirements And creating pipelines for them.

Soft skills such as communication, leading the team, taking ownership and accountability to successful engagement.

Participate in quality management reviews

Managing customer expectation and business user interactions

Deliver key research (MVP, POC) with an efficient turn-around time to help make strong product decisions.

Demonstrate key understanding and expertise on modern technologies, architecture, and design. Mentor the team to deliver modular, scalable, and high-performance code.

Be a change agent on key innovation and research to keep the product, team at the cutting edge of technical and product innovation.