Über
Please ensure candidates are screened heavily for hands-on PySpark, PANDA, SQL coding ability, and real ML implementation experience before submission.
SQL: THIS IS HER TOP TOP MUST HAVE!! Must be able to write and execute SQL queries independently. THEY WILL BE TESTED ON THIS ONSITE- Strong hands-on ability is required, including data extraction and basic to intermediate transformations.
Interview Format: In-person interview only (no video interviews).
Candidates should be prepared for live SQL and PySpark problem-solving, as many candidates struggle with hands-on coding in person.- PLEASE MAKE SURE YOUR CANDIDATES ARE LOCAL AND CAN COME ONSITE.
Required Certifications: Databricks Data Engineer certification is MOST IMPORTANT but can be completed post-onboarding. Google Cloud certification is also acceptable post-hire. PySpark (Highest Priority): Core requirement of the role. Candidates must have strong hands-on experience building data pipelines and performing large-scale data processing. Python / Pandas: Required for data cleaning, transformation, and analysis. Machine Learning (20% of role): Candidates must already have hands-on ML experience (classification, regression, clustering, model evaluation). No training will be provided on ML concepts. Data Analysis Focus: Majority of the role involves SQL-based data extraction and PySpark/Pandas-driven analysis and insights ML + Analytics Integration: Candidates should understand end-to-end workflows combining SQL, PySpark, and ML. Team Structure: Approximately 10 Data Engineers and 6 Data Scientists within the team.
Sprachkenntnisse
- English
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