Design technical solutions for data acquisition and storage into our centralized data repository.
Develop ELT scripts design datadriven 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 adhoc data loads.
Provide the data quality check and report on the data quality issue.
Requirements
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 AIdriven insights into data pipelines.
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