Description

Required skills include:

• Data extraction
• Joins, aggregations, and filtering
• Basic to intermediate data transformations
• Strong hands-on coding ability

Interview Format

• In-person interviews only (NO video interviews)
• Candidates must be local and available to attend onsite interviews
• Live SQL and PySpark coding exercises will be conducted during the interview process
• Many candidates struggle with hands-on coding, so please validate technical skills thoroughly before submission

Certifications

• Databricks Data Engineer Certification is highly preferred and considered the most important certification
• Certificatio1n can be completed post-onboarding if not currently held
• Google Cloud (GCP) Certification is also acceptable and may be completed after hire

PySpark (Highest Priority Technical Skill)

Candidates must have strong hands-on experience with:

• Building and maintaining data pipelines
• Large-scale data processing
• Data transformation and optimization
• Working within distributed data environments

Python / Pandas

Required experience includes:

• Data cleansing and preparation
• Data transformation
• Exploratory data analysis
• Data manipulation using Pandas

Machine Learning (Approximately 20% of the Role)

Candidates must already possess hands-on Machine Learning experience. No ML training will be provided.

Required experience includes:

• Classification models
• Regression models
• Clustering techniques
• Model evaluation and performance measurement

Data Analytics Focus

The majority of the role will involve:

• SQL-based data extraction and analysis
• PySpark data processing
• Pandas-driven analysis
• Generating business insights from large datasets

End-to-End Analytics Experience

Candidates should understand complete workflows that integrate:

• SQL
• PySpark
• Python/Pandas
• Machine Learning models and analytics

Team Structure

• 10 Data Engineers
• 6 Data Scientists

Key Skills

Education

Bachelor's degree