Job Summary
We are seeking a highly analytical and experienced Principal Data Analyst to lead advanced data analysis, generate actionable business insights, and support data-driven decision-making across the organization. The role will be responsible for analyzing complex datasets, developing analytical models and dashboards, identifying trends and patterns, and providing strategic recommendations to business and technical stakeholders.
Key Responsibilities
Lead complex data analysis projects and provide actionable insights to support strategic and operational decision-making.
Collect, clean, validate, transform, and analyze data from multiple sources.
Develop and maintain analytical models, reports, dashboards, and data visualizations.
Identify trends, patterns, anomalies, and relationships within large and complex datasets.
Translate business requirements into analytical solutions and measurable data-driven outcomes.
Perform advanced statistical and exploratory data analysis to support business planning and performance improvement.
Develop and monitor key performance indicators (KPIs) and analytical metrics.
Work closely with business, IT, engineering, finance, operations, and other teams to understand data requirements and provide analytical support.
Ensure data accuracy, consistency, completeness, and reliability across analytical outputs.
Develop SQL queries and analytical processes to extract and manipulate data from databases and other data sources.
Identify opportunities to improve data collection, reporting, analytics processes, and data quality.
Present complex analytical findings and recommendations clearly to both technical and non-technical stakeholders.
Provide technical guidance and mentorship to junior and mid-level data analysts.
Support forecasting, predictive analysis, business planning, and performance measurement initiatives.
Maintain appropriate documentation of analytical methodologies, data sources, models, and reporting processes.
Educational Requirements
Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or a related field.
Additional training or certification in Data Analytics, Data Science, Business Intelligence, Statistics, or a related area is an advantage.
Relevant Core Competencies
Data Analysis:
Strong ability to analyze large, complex, and diverse datasets and convert data into meaningful insights.
SQL & Databases:
Advanced SQL skills and strong understanding of relational databases, data extraction, transformation, and querying.
Data Visualization:
Proficiency in developing clear and effective dashboards and visualizations using tools such as Power BI, Tableau, or similar platforms.
Programming & Analytics:
Strong knowledge of Python, R, or other programming and analytical tools used for data processing and analysis.
Statistical Analysis:
Strong understanding of statistics, data modeling, forecasting, trend analysis, and hypothesis testing.
Business Intelligence:
Ability to translate business questions and requirements into measurable analytical solutions and KPIs.
Data Quality:
Strong understanding of data validation, data cleaning, data integrity, and data quality management.
Problem Solving:
Excellent analytical and critical-thinking skills with the ability to investigate complex problems and develop practical solutions.
Communication:
Ability to communicate complex technical and analytical concepts clearly to both technical and non-technical audiences.
Strategic Thinking:
Ability to connect analytical findings with organizational objectives and provide strategic recommendations.
Attention to Detail:
High level of accuracy and attention to detail when working with data, reports, and analytical models.
Leadership & Mentorship:
Ability to guide, mentor, and provide technical support to other analysts and team members.
Stakeholder Management:
Strong ability to collaborate with cross-functional teams and manage analytical requirements from different stakeholders.
Technical Skills
Advanced SQL and database management.
Data visualization and business intelligence tools such as Power BI or Tableau.
Python, R, or other data analysis programming languages.
Microsoft Excel, including advanced formulas, PivotTables, and data analysis features.
Understanding of data warehousing, ETL processes, and data integration concepts.
Knowledge of statistical and analytical methodologies.
Familiarity with cloud-based data platforms and modern analytics technologies is an advantage.
Personal Qualities
Highly analytical, proactive, and results-oriented.
Strong organizational and time-management skills.
Ability to work independently and collaboratively.
Strong professional judgment and decision-making ability.
Curious and continuously willing to learn new technologies and analytical techniques.
Strong integrity when handling confidential and sensitive data.
Apply for this Job