Technical Mastery: Strong proficiency in Azure Cloud Platform, particularly Databricks, Synapse Analytics, Data Factory and Data Lake Storage, Azure SQL, and multi-dimensional data warehouse methodology.
ETL Proficiency: Experienced in building ETL (Extract, Transform, Load) workflows that support efficient data movement and processing in cloud environments. Familiarity with sourcing data from leading Saas providers and their API solutions such as Oracle Fusion Cloud ERP, Salesforce CRM and CSM, Workday HCM and relational databases like Oracle, MS SQL Server and Postgres.
Data Transformation Skills: Deep understanding of data transformation techniques to ensure accuracy and performance across all systems.
Cloud Infrastructure Knowledge: Proficiency with Azure cloud infrastructure management and best practices for data security, scalability, and cost efficiency.
Analytical Problem-Solving: Ability to troubleshoot data issues and proactively improve processes to enhance data reliability.
Code Optimization: Advanced skills in writing and optimizing complex Python, Java, JSON, Spark and SQL queries for better performance and throughput.
Data Modeling Expertise: Proven experience developing efficient data models that support large-scale analytics.
Reporting, Analytics and Visualization: Proficiency in Analytics and visualization tools like Power BI, Tableau and Oracle Analytics Cloud.
Data Governance: Strong knowledge of data governance practices, including data quality, lineage, data at rest and in-transit security and role-based access control protocols.
Collaborative Communication: Ability to work cross-functionally with data scientists, analysts, visualization teams and business users to deliver comprehensive insights.
LIMS Familiarity: Familiarity with Laboratory Information Management Systems (LIMS) such as Sunquest Antrim and Sysmex MOLIS is a big plus.
AI/ML Experience: Familiarity with applying machine learning models to data processes and enhancing data pipeline functionality.