Establish scalable, efficient, automated processes for data analysis, data model development, validation, and implementation.
Work closely with analysts/data scientists to understand impact to the downstream data models.
Write efficient and well-organized software to ship products in an iterative, continual release environment.
Contribute to and promote good software engineering practices across the team
Communicate clearly and effectively to technical and non-technical audiences.
Minimum Qualifications:
University or advanced degree in engineering, computer science, mathematics, or a related field
Strong hands-on experience in Databricks using PySpark and Spark SQL (Unity Catalog, workflows, Optimization techniques)
Experience with at least one cloud provider solution (GCP preferred)
Strong experience working with relational SQL databases.
Strong experience with object-oriented/object function scripting language: Python.
Working knowledge in any transformation tools, DBT preferred.
Ability to work with Linux platform.
Strong knowledge of data pipeline and workflow management tools (Airflow)
Working knowledge of Git hub /Git Toolkit
Expertise in standard software engineering methodology, e.g. unit testing, code reviews, design documentation
Experience creating Data pipelines that prepare data for ingestion & consumption appropriately.
Experience in maintaining and optimizing databases/filesystems for production usage in reporting, analytics.
Working in a collaborative environment and interacting effectively with technical and non-technical team members equally well. Good verbal and written communication skills.