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 wellorganized 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 nontechnical audiences.
Minimum Qualifications:
University or advanced degree in engineering computer science mathematics or a related field
Strong handson 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 objectoriented/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 nontechnical team members equally well. Good verbal and written communication skills.
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