Key Responsibilities :

Python Proficiency :

- Demonstrate strong command of Python, actively contributing to the development and enhancement of data engineering solutions.

Data Engineering Expertise :

- Build and manage efficient and scalable data pipelines.

- Work with SQL, Data Warehouses, and Data Lakes to ensure robust data integration.

- Perform data cleansing and implement validation techniques to ensure high data integrity.

Tool and Platform Proficiency :

- Must have hands-on experience with Databricks.

- Experience with additional data engineering platforms/tools is a plus.

- Stay updated with industry trends and continuously improve data processes.

Collaboration and Communication :

- Work closely with data scientists, analysts, and software engineers to align on data strategies.

- Clearly communicate technical insights to non-technical stakeholders.

Documentation and Best Practices :

- Maintain thorough documentation for data workflows and infrastructure.

- Promote and implement data engineering best practices.

Must-Have Skills :

- Bachelor's or Master's degree in Engineering (B.Tech, BE, M.Tech, ME) in any field.

- At least 3 years of hands-on experience as a Data Engineer.

- Strong proficiency in Python and SQL.

- Experience with Databricks and managing data pipelines, data warehouses/lakes.

- Strong analytical, problem-solving, and critical thinking skills.

Nice-to-Have Skills (Optional) :

- Experience with cloud platforms (AWS, Azure, GCP) and PySpark.

- Familiarity with big data tools such as Hadoop, Spark, Snowflake.

- Understanding of containerization tools like Docker or Kubernetes.

- Interest or experience in data visualization tools (Power BI, Tableau).

- Certifications in data engineering, cloud, or ML technologies.