Junior Big Data Engineer

Role Overview

This role is for an early-career engineer who wants to grow in modern data engineering while working close to practical AI use cases. You will help build reliable pipelines, organize messy operational data, and prepare datasets that make analytics, automation, and AI agents useful inside real businesses.

What You Will Do

• -Build and maintain batch and streaming data pipelines using Python, SQL, and cloud data tools.
• -Support data ingestion, transformation, validation, and quality checks across structured and semi-structured sources.
• -Work with senior engineers to design analytics-ready datasets, feature pipelines, and reporting layers.
• -Document data flows, assumptions, and operational handoffs so client teams can maintain what we build.
• -Troubleshoot pipeline failures, data quality issues, and performance bottlenecks.

What We Are Looking For

• -Hands-on experience with Python and SQL through coursework, projects, internships, or professional work.
• -Familiarity with ETL/ELT concepts, data modeling basics, and cloud data platforms.
• -Interest in big data tools such as Spark, PySpark, Databricks, Snowflake, BigQuery, or similar platforms.
• -Comfort learning new systems quickly and asking clear questions when requirements are ambiguous.
• -Strong attention to detail and a bias toward clean, maintainable work.

Nice To Have

• -Exposure to orchestration tools such as Airflow, Dagster, Prefect, or dbt.
• -Experience supporting AI, machine learning, or analytics projects.
• -Basic understanding of APIs, file formats, and data governance practices.