Key Responsibilities

- Assist in developing and maintaining data pipelines using Databricks.
- Work with Python, PySpark, and SQL for data processing and transformation.
- Assist in developing and maintaining ETL/ELT workflows.
- Work with Delta Lake and Databricks Lakehouse concepts.
- Perform data extraction, transformation, cleansing, and validation.
- Write SQL queries for data transformation, analysis, and data validation.
- Process structured and semi-structured data such as CSV, JSON, and Parquet.
- Assist in monitoring and troubleshooting data pipeline issues.
- Support data quality checks and validation processes.
- Participate in testing and documenting data pipelines.
- Collaborate with senior data engineers and technical teams.
- Follow best practices for coding, version control, testing, and deployment.
- Continuously learn and adapt to new data engineering technologies and tools.

Required Skills

- Bachelors degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.




- Solid fundamentals in Python.
- Good knowledge of SQL.
- Basic to intermediate knowledge of PySpark / Apache Spark.
- Hands-on knowledge or academic/project experience with Databricks.
- Basic understanding of ETL/ELT concepts and data pipelines.
- Understanding of databases and basic data warehousing concepts.
- Good analytical and problem-solving skills.
- Strong willingness to learn and work in a data engineering environment.

Preferred Skills

- Knowledge of Delta Lake and Databricks Lakehouse architecture.
- Basic knowledge of Azure, AWS, or GCP.
- Familiarity with Git/GitHub.
- Exposure to Databricks Workflows/Jobs.
- Basic knowledge of data orchestration tools such as Azure Data Factory or Airflow.
- Experience working with APIs and JSON data.
- Academic or personal projects involving Databricks, PySpark, and SQL.

📌 Junior Data Engineer (India)
🏢 Zephico Technologies
📍 India