Responsibilities:

• Design technical solutions for data acquisition and storage into our centralized data repository.
  
• Develop ELT scripts, design data-driven logic and conduct unit testing.
  
• Conduct database modeling and design as to improve overall performance.
  
• Produce design artifacts and documentation which will allow future support of the implemented solutions.
  
• Investigate and resolve incidents and identify whether the problem is caused by the data loading code or is due to bad data received from the data provider.
  
• Execute service requests related to routine and ad-hoc data loads.
  
• Provide the data quality check and report on the data quality issue.
  

MUST HAVES:

10+ years experience in:

• Designing and developing scalable Medallion Data Lakehouse architectures.
  
• Expertise in data ingestion, transformation, and curation using Delta Lake and Databricks.
  
• Experience integrating structured and unstructured data sources into star/snowflake schemas.
  
• Building, automating, and optimizing complex ETL/ELT pipelines using Azure Data Factory (ADF), Databricks (PySpark, SQL, Delta Live Tables), and dbt.
  
• Implementing orchestrated workflows and job scheduling in Azure environments.
  
• Strong knowledge of relational (SQL Server, Synapse, PostgreSQL) and dimensional modeling.
  
• Advanced SQL query optimization, indexing, partitioning, and data replication strategies.
  
• Experience with Apache Spark, Delta Lake, and distributed computing frameworks in Azure Databricks.
  
• Working with Parquet, ORC, and JSON formats for optimized storage and retrieval.
  
• Deep expertise in Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure SQL, Event Hubs, and Azure Functions.
  
• Strong understanding of cloud security, RBAC, and data governance.
  
• Proficiency in Python (PySpark), SQL, and PowerShell for data engineering workflows.
  
• Experience with CI/CD automation (Azure DevOps, GitHub Actions) for data pipelines.
  
• Implementing data lineage, cataloging, metadata management, and data quality frameworks.
  
• Experience with Unity Catalog for managing permissions in Databricks environments.
  
• Expertise in Power BI (DAX, data modeling, performance tuning).
  
• Experience in integrating Power BI with Azure Synapse and Databricks SQL Warehouses.
  
• Familiarity with MLflow, AutoML, and embedding AI-driven insights into data pipelines.
  
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