05 · Data & AI
Data Engineer
Pipelines that move and shape data at scale
- Fresher (India)
- ₹4 – 8 LPA
- Demand
What it is
Analysts and models are useless without clean data arriving on time. Data engineers build the pipelines (ETL / ELT) that pull data from apps, transform it, and load it into warehouses — reliably, every day, at scale.
What you actually do all day
- 1Build and schedule ETL / ELT pipelines
- 2Design warehouse schemas and data models
- 3Process large datasets with distributed tools
- 4Monitor pipeline failures and data quality
Core tech stack
Core
- SQL (advanced)
- Python
- Linux
Pipelines
- Airflow
- dbt
- Kafka
- Spark
Warehouse
- Snowflake
- BigQuery
- Redshift
Reality check: Strongest demand of the three data roles, but very SQL-heavy day to day.
Good fit if: You like plumbing, reliability and systems that must not break at 3 am.
Your first step
Build a pipeline that pulls from a public API daily, transforms it, and loads it into a warehouse.