Sr. Data Analyst

Key Responsibilities

• Design, implement, and maintain scalable data pipelines for the extraction, transformation, and loading (ETL) of large datasets
• Create algorithms and statistical models to extract actionable insights.
• Design, develop and implement data models for base tables and dashboards
• Conduct thorough analysis to understand data models, upstream source systems, and trends within datasets
• Query massive data sets to interpret complex relations
• Build complex logics for attributes, metrics and feature banks under engineered datasets and reports
• Leverage GenAI capabilities and machine learning techniques to enhance data analysis capabilities.
• Enable and/or develop AI use cases (ML or GenAI based)
• Test, vet, deploy, maintain and monitor AI pipelines
• Create visualizations and dashboards to communicate data-driven insights.
• Package and serve data products over the various reporting outlets in use
• Adhere to information security and personal data privacy mandates and guidelines in data collection, analysis, access management and reporting
• Implement best practices for data governance, quality and documentation
• Implement best practices and continuously improve data analytics processes
• Develop and maintain data architecture and data management, ensuring data integrity, security, and optimal performance

Education

Bachelor's degree in IT, Computer Engineering, Computer Science, Data Science

Level of Experience

Limited Experience (2-5Yrs) in a related field

Technical Skills & Knowledge

Essential

• Excellent knowledge of data warehousing and data modelling principle
• Excellent knowledge SQL
• Very good knowledge of Linux and OS Administration
• Excellent knowledge of Python
• Working knowledge of orchestration platforms (e.g. Airflow)

Desirable

• Good knowledge of telecom core systems and data sets
• Good knowledge of key information security and networking principles
• Good knowledge of Scala
• Good knowledge of spark framework

Certifications & Licensure

Essential

• SQL (any variant) Certification
• Python Certification
• Hadoop or Data Lakehouse Certification

Desirable

• GenAI and LLM Engineering Certification
• Spark Certification
• Airflow Certification

Tools & Systems

Essential

• Data Warehousing or modern data platform
• Apache Hadoop eco-system
• Power BI (or other visualization tools)
• Python (base, pandas, scikit-learn)
• Agentic Development

Desirable

• GenAI e2e solutions development