About the Role :

We're looking for a Data Engineer with 1 - 2 years of experience to join our data team. You'll help build, maintain, and optimize data pipelines that power analytics and decision-making across the organization. This is a great opportunity for someone early in their career who wants to deepen their skills in workflow orchestration, data pipeline design, and Python-based data engineering.

Key Responsibilities :

- Design, build, and maintain ETL/ELT data pipelines using Apache Airflow.

- Write clean, efficient, and reusable Python code for data processing and transformation.

- Use Jupyter Notebooks for data exploration, prototyping, and validation of pipeline logic.

- Monitor pipeline performance, troubleshoot failures, and ensure data quality and reliability.

- Collaborate with data analysts, data scientists, and other engineers to understand data requirements.

- Maintain and improve existing DAGs, including scheduling, dependency management, and error handling.

- Document pipelines, workflows, and processes for team-wide visibility.

- Assist in optimizing SQL queries and database performance where needed.

Required Skills & Qualifications :

- 1 - 2 years of hands-on experience in data engineering or a related role.

- Proficiency in Apache Airflow (DAG creation, scheduling, operators, task dependencies).

- Strong working knowledge of Python for scripting and data manipulation.

- Experience using Jupyter Notebook for data analysis/prototyping.

- Familiarity with SQL and relational databases.

- Understanding of ETL/ELT concepts and data pipeline best practices.

- Basic knowledge of version control (Git).

Nice to Have :

- Experience with cloud platforms (AWS / GCP / Azure).

- Familiarity with data warehousing tools (Snowflake, BigQuery, Redshift, etc.).

- Exposure to libraries like Pandas, NumPy, or PySpark.

- Understanding of data modeling concepts.

- Experience with containerization (Docker).