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Job Description
Structured overview of role & requirementsAbout This Role
Design and implement enterprise-scale data engineering and architecture solutions across cloud and hybrid environments using Azure Data Stack and related technologies.
Build and optimize data integration and ETL/ELT pipelines employing Microsoft Fabric, Azure Data Factory, Databricks, Synapse, SQL, Python, and Spark.
Lead technical decisions, architecture design reviews, and collaborate with stakeholders to ensure data governance, data quality, and security standards are implemented across platforms.
Minimum Requirements
Proven experience in Data Engineering, Data Architecture, and Data Governance with ability to deliver end-to-end enterprise data solutions.
Hands-on expertise with Microsoft Fabric, Azure Data Factory, Databricks, Azure Synapse Analytics, SQL, Python, and Spark.
Strong understanding of data lakes, lakehouse architecture, data warehouses, ETL/ELT frameworks, and cloud data platforms.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in architecting scalable data solutions leveraging the Azure Data Stack and integrating multiple data sources such as Oracle, SAP, Salesforce, and PostgreSQL.
Possesses technical leadership skills including design reviews, performance optimization, and stakeholder management in data engineering projects.
Has knowledge or exposure to additional cloud platforms (AWS, GCP), Airflow, and BI/reporting tools like Power BI, indicating a broad and adaptable skill set.