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
Job Title
Data Architect