- Microsoft Fabric
- Azure Data Factory (ADF)
- Azure Data Lake Storage Gen2 (ADLS)
- Azure Databricks
- Python / PySpark
- SparkSQL
- SQL
- Data Engineering / ETL / ELT
Key Accountabilities:
- Lead development of enterprise-scale solutions using Microsoft Fabric and Azure Data Services.
- Design and implement Fabric Lakehouse, Warehouse, Data Factory, Data Pipelines, Notebooks and OneLake solutions.
- Build AI-enabled applications using Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Microsoft Foundry.
- Define data architecture, integration patterns and governance frameworks.
- Apply data modelling skills to design conceptual,
logical and physical data models aligned to banking domain entities (Customer, Account, Transaction, etc).
- Develop Bronze, Silver and Gold data models, along with data quality controls and analytical data structures, to support reporting, governance, APIs and AI use cases.
- Establish coding standards, design reviews and engineering best practices.
- Ensure scalability, performance, security and operational excellence.
- Mentor engineering teams and oversee technical delivery.
- Apply banking domain knowledge to banking data structures like customer, transaction, risk, fraud and compliance other data solutions.
Valuable to Have:
- Azure Synapse / Snowflake
- Power BI
- Azure OpenAI / Azure AI Search / AI Document Intelligence
- Microsoft Foundry
- BFSI / Banking domain experience
- Azure DevOps / CI/CD
📌 Data Engineer (Hyderabad)
🏢 ValueMomentum
📍 Hyderabad
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