Data Analyst

About the Role

We are looking for a highly motivated Data Analyst / Data Engineer with 2+ years of experience in data transformation, analysis, and visualization. The ideal candidate should have a solid understanding of SQL, data modeling, ETL processes, and business intelligence tools.

You will work on designing, building, and optimizing datasets and analytical solutions for e-learning and business intelligence reporting.

Key Responsibilities

• Design and develop data pipelines for ingestion, transformation, and reporting using SQL and Python.
• Create and maintain analytical tables, views, and materialized views for dashboarding and advanced analytics.
• Perform in-depth data analysis and validation to ensure data integrity and accuracy.
• Collaborate with stakeholders to translate business requirements into technical solutions.
• Develop interactive dashboards and reports using tools like Power BI or Tableau.
• Optimize database performance (indexing, partitioning, query tuning).
• Work closely with the data engineering team to improve ETL workflows and data quality monitoring.

Required Skills & Qualifications

• 24 years of professional experience in data analytics or data engineering.
• Strong proficiency in SQL (PostgreSQL, MySQL).
• Experience with ETL tools (Airflow, Dataform, or custom Python pipelines).
• Working knowledge of Python (Pandas, NumPy) for data transformation.
• Experience with data visualization tools such as Power BI
• Understanding of data modeling concepts (star/snowflake schema).
• Familiarity with cloud databases (Azure, GCP) preferred.
• Strong analytical mindset and ability to work independently.

Good-to-Have

• Experience with BigQuery, Azure Data Studio, or dbt.
• Exposure to API-based data extraction and automation workflows.
• Knowledge of data governance and version control (Git).
• Interest in LMS analytics, e-learning data, or edtech domain.

What Youll Gain

• Opportunity to work on end-to-end analytics lifecycle from data ingestion to visualization.
• Exposure to enterprise-level data ecosystems and reporting architectures.
• Learn modern data engineering best practices and cloud integrations.
• Work on projects impacting learning outcomes and education insights at scale.