Data Analytics – SQL & Large-Scale Data Analysis

Requirements:

• Strong experience in SQL and large-scale data analysis, preferably within the telecommunications domain.

• Proficient in writing complex SQL queries for:

  • Data extraction from large datasets
  • JOIN across multiple tables and data sources
  • Aggregation using functions such as GROUP BY, COUNT, SUM, AVG, etc.
  • Filtering and conditional analysis
  • Time-based analysis using date/time functions
  • Subqueries, CTEs, and window functions

• Strong ability to analyze large-volume and high-dimensional telecom datasets efficiently.

• Experienced in analyzing time-series data to identify trends, patterns, anomalies, and performance changes over specific periods.

• Able to combine and analyze data from multiple sources, such as network KPI/PM, CDR/xDR, OSS/NMS, traffic, and customer experience data.

• Understand data structures and relationships across large relational databases.

• Able to perform data validation, cleansing, transformation, and aggregation using SQL.

• Familiar with query optimization and efficient data retrieval when working with large datasets.

• Able to identify data quality issues, inconsistencies, missing data, and anomalies during analysis.

• Experience working with data warehouses, data lakes, or big-data environments is an advantage.

• Familiar with Python, Excel, or BI/Data Visualization tools for further analysis and reporting.

• Strong analytical and problem-solving skills with the ability to translate large-scale data into actionable insights.

• Able to clearly communicate analytical findings to both technical and non-technical stakeholders.

Key Competency:

SQL & Large-Scale Data Analysis — Strong proficiency in SQL for extracting, joining, filtering, aggregating, and performing time-based analysis on large-scale telecommunications datasets, with the ability to derive meaningful insights from complex and multi-source data.