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.ref : hirist.tech)