About the role
We are looking for a skilled and passionate Data Engineer to join our growing data team. The ideal candidate will have strong experience in building scalable data pipelines and modern cloud-based data platforms using Databricks, Azure, Snowflake, and PythonThe role involves working closely with cross-functional teams to design, develop, and optimize data solutions that support analytics and business intelligence initiatives.
Responsibilities:
- Design, build, and maintain scalable ETL/ELT pipelines using Databricks and Python.
- Develop and optimize data workflows on the Azure cloud platform.
- Work extensively with Snowflake for data warehousing, performance tuning, and data transformations.
- Write efficient and reusable Python code with a strong understanding of string manipulation and data processing techniques.
- Integrate data from multiple structured and unstructured data sources.
- Monitor and troubleshoot data pipelines to ensure reliability and performance.
- Collaborate with data architects, analysts, and business stakeholders to understand data requirements.
- Implement best practices around data quality, governance, and security.
- Participate in code reviews, deployment processes, and production support activities.
Requirements:
- 5+ years of experience in Data Engineering.
- Strong hands-on experience with Databricks.
- Good experience working on Azure Cloud services.
- Strong knowledge of Snowflake.
- Strong programming skills in Python.
- Good understanding of string handling/manipulation in Python.
- Experience with SQL and data transformation techniques.
- Knowledge of ETL/ELT frameworks and orchestration tools.
- Experience working with large-scale datasets and distributed data processing.
Preferred Skills:
- Experience with PySpark.
- Exposure to CI/CD pipelines and DevOps practices.
- Knowledge of data modeling concepts.
- Familiarity with Agile methodology.