Expertise in cloud-native data platforms (AWS, Azure, or GCP) and their Gen AI-related
services (e.g., Amazon Bedrock, Azure OpenAI Service, Google Vertex AI).
Ability to evaluate and recommend new and emerging Gen AI data technologies and tools to
drive innovation.
Deep knowledge and hands on experience in design and implementation of Big Data technologies (Apache Spark, Apache Flink, Databricks, Apache Airflow, Hadoop ecosystem, Streaming data, DevOps, Observability, Data lineage, Data Cataloging, Data Security, Data Governance, LLMs, SLM, AI, ML Modelling) and familiarity with data architecture patterns (data warehouse, data lake, lakehouse, data ingestion, curation and consumption)
Define and enforce Data Governance frameworks
Familiarity with databases and analytics technologies in the industry including Data Warehousing/ETL, Relational Databases, or MPP.
Expertise in metadata management, reference data management.
Experience with cloud providers such as Azure, AWS (preferably Azure) and their native services for ingestion, ELT/ ETL and consumption
Build data pipelines for multiple storage solutions, including distributed platforms such as
Databricks, Trino, Hadoop and MPP databases and cloud Data warehouse
Design and implement low latency analytical platform services leveraging open source and
cloud technology

Data Architect