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Junior Data Engineer

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Job Description - Junior Data Engineer


Job Description: Data Analyst/Data Engineer (2+ Years Experience)

Type: Full-time

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

·       2–4 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 You’ll 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.

 







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