Description

You will own end-to-end analytics workflows, integrating SQL, PySpark, Python, and machine learning to generate business insights from large datasets.

This role is on-site.

Responsibilities

• Build and maintain scalable data pipelines using PySpark for large-scale processing and optimization.
• Perform complex data extraction, joins, aggregations, and filtering using advanced SQL.
• Execute data cleansing, preparation, and exploratory analysis using Python and Pandas.
• Develop, evaluate, and deploy machine learning models including classification, regression, and clustering.

Required Skills

• Strong hands-on experience with PySpark, including building data pipelines and distributed data environments.
• Proficiency in SQL for complex queries, data extraction, and analysis.
• Expertise in Python and Pandas for data manipulation, transformation, and analysis.
• Proven experience in machine learning, specifically classification, regression, clustering, and model evaluation.
• 5+ years of relevant experience in data analytics or engineering.
• Bachelor's degree in a technical field.
• Ability to pass live SQL and PySpark coding exercises during in-person interviews.

Preferred Skills

• Databricks Data Engineer Certification (can be completed post-onboarding).
• Google Cloud (GCP) Certification (can be completed post-hire).

Key Skills

Education

Bachelor's degree