Data Architect
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Role: Data and AI Architect
Key Skills to Succeed in this role
• Strong hands-on background in data engineering, analytics, or data science.
• Expertise in building data platforms using:
o Cloud: AWS (Glue, S3, Redshift), Azure (Data Factory, Synapse), GCP (BigQuery,
Dataflow).
o Compute: Spark, Databricks, Flink.
o Data modelling: dimensional, relational, NoSQL, graph.
• Proficiency with Python, SQL, and data pipeline orchestration tools.
• Understanding of ML frameworks and tools: TensorFlow, PyTorch, Scikit-learn, MLflow, etc.
• Experience implementing MLOps, model deployment, monitoring, logging, and versioning.
Preferred Qualifications
• 8+ years of experience in data engineering, data science, or architecture roles.
• Experience designing enterprise-grade AI platforms.
• Certification in major cloud platforms (AWS/Azure/GCP).
• Experience with governance tooling (Collibra, Alation) and lineage systems
Job ID: 136586841
Skills:
data vault , data products , kimball , Metadata Management, Pyspark, Azure Databricks, ELT, Quality, Data Governance, Data Modelling, Power Bi, Azure Data Factory, Spark, Data Lake, Rest Apis, Etl, Purview, lineage, Google BigQuery, Security, SQL Warehouses, Lakehouse architectures, Data APIs, Unity Catalog, dimensional modelling, Dataplex, Databricks Delta Sharing
Skills:
snowflake , Adb, Adf, Power Bi, Pyspark, Kafka, Tableau, Sql, Spark Streaming, Databricks, Python, Azure SQL Data Lake, Synapse, Event Hubs, Microsoft Fabric, Azure Data Services
Skills:
Restful Apis, LLMs and AI ML technologies, Portfolio Management systems, buy-side financial services technologies, Investment Book of Record accounting systems, MS T-SQL
Skills:
Technical Architecture, Agentic AI Frameworks, Generative AI LLMs RAG, Cloud Platforms Azure AWS GCP, MLOps DevOps, Agile Scrum Delivery, Data Pipelines, AI Machine Learning
Skills:
Sql, Python, Snowflake Data Warehouse, dbt, Fivetran
