Data Engineer (Python)
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Before you apply
LocationUNAVAILABLE, UNAVAILABLE, UNAVAILABLE
SenioritySenior
Experience4+ yrs
Company size8+ people
PostedOct 30, 2024 · 2y ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on Oct 30, 2024100% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
Kimball methodology experience designing and building dimensional data warehouses
Dataform expertise for developing, testing, and deploying SQL-based data transformation workflows
Expert-level SQL including window functions, CTEs, and complex joins
Deep hands-on experience with Google BigQuery including performance tuning, cost optimization, and partitioning/clustering
Strong practical knowledge of data warehousing schemas (Star Schema, Snowflake Schema, Data Marts)
Ability to analyze and profile datasets to derive insights and assess quality
Experience preparing data for consumption by BI tools like Looker, Tableau, or Power BI
Proficiency in using Git for managing SQL and Dataform code
4 years of experience needed
Experience with building and deploying machine learning models using BQML
Skills
Google BigQuery
Dataform
Python
Git
Looker
Tableau
Power BI
Overview
We are seeking a highly skilled Data Engineer to own the transformation and modeling layers of a new data warehouse project. This role is centered around an expert-level mastery of Google BigQuery (including Dataform). You will be responsible for taking raw data and architecting clean, reliable, and performant data models by applying Kimball methodology principles to power business intelligence and analytics. Your expertise in building sophisticated, scalable transformation pipelines with Dataform will be vital in transforming complex datasets into actionable insights and ensuring the analytical integrity of our dimensional data warehouse.
Responsibilities
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Lead the development, maintenance, and optimization of the entire data transformation lifecycle using Dataform to produce high-quality, trusted datasets.
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Build and manage scalable, well-documented, and tested data transformation pipelines that are critical for business reporting.
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Conduct Exploratory Data Analysis (EDA) on new and existing datasets to identify quality issues, understand data structures, and unlock business value.Write highly performant BigQuery SQL for complex queries, aggregations, and data manipulation, with a focus on cost and speed optimization.
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Implement rigorous data quality and validation checks within the transformation process to ensure accuracy and trust in our reporting datasets.
Qualifications
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Kimball Methodology: Demonstrable, in-depth experience designing and building dimensional data warehouses using Kimball’s principles.
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Dataform Expertise: Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment.
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Expert-Level SQL: Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins.
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Google BigQuery: Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering.
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Database Schema Concepts: Strong, practical knowledge of data warehousing schemas (Star Schema, Snowflake Schema, Data Marts).
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Exploratory Data Analysis (EDA): Ability to analyze and profile datasets to derive insights and assess quality.
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Business Intelligence (BI) Tool Integration: Experience preparing data for consumption by BI tools like Looker, Tableau, or Power BI.
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BigQuery ML (BQML): Experience with building and deploying machine learning models using BQML is a significant plus.
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Version Control (Git): Proficiency in using Git for managing SQL and Dataform code.
Required Skills
Google BigQuery (2), Python (4), Gemini Enterprise (1), Artificial Intelligence (AI) (1)
Years of Experience Needed
4