Lead Azure Data Engineer

Job Description:

Responsibility:

. Lead cross-functional data analytics teams through the successful planning, execution of projects within scope, budget, and timeline constraints.

. Develop design solutions, defining tasks, timelines, and resource needs.

· Facilitate communication and collaboration among stakeholders, fostering strong project goals and priorities.

· Analyze various data elements and huge datasets by writing effective sql queries and code to understand customer data and present data for decision-making.

· Lead the design and development of regulatory use cases and data requests.

· Design a standardized architecture incorporating tools from data analytics and establish a reusable framework that ensures consistency, scalability, and efficiency, team adoption across initiatives.

· Identify and mitigate project risks, proactively resolving issues to prevent potential problems.

· Monitor project progress and performance, providing weekly regular updates and transparency and accountability.

· Design new data pipelines and data models and spearhead the comprehensive redesign of underperforming data pipelines, implement enhancements to address existing inefficiencies, improve performance there by creating a robust solution.

· Develop and implement big data analytical projects using Python, Spark, Machine validation processes to ensure accuracy, quality compliance, and reliability of developed solutions.

· Perform data profiling, governance, data quality checks, encryption etc. for high-quality data reliability.

· Conduct feasible assessments and provided technical recommendations for the data solutions.

Preferred education:

Bachelor’s and or Masters in Computer Science/ Information Technology.

Technical Skills:

SQL: Expert knowledge of SQL for data manipulation and querying within databases.

Data Visualization Tools: Proficiency in tools like Power BI, MicroStrategy to create impactful data visualizations.

Programming Languages: Familiarity with Python or R for advanced data analysis and modeling.

Machine Learning: Understanding of machine learning concepts and ability to apply them to relevant data analysis problems.

Data Warehousing & ETL: Knowledge of data warehousing systems and data extraction, transformation, and loading (ETL) processes in Azure Cloud.

Leadership & Communication Skills:

Team Management: Ability to lead and mentor a team of data analysts, assigning tasks and providing guidance.

Stakeholder Management: Effectively communicating complex data insights to non-technical stakeholders.

Presentation Skills: Presenting data findings in a clear and concise manner to various audiences.

Cross-Functional Collaboration: Working effectively with teams across different departments to gather requirements and implement data solutions.