Description

You will design, develop, and maintain data systems and machine learning models while integrating them into existing technical infrastructure. You will own the ETL pipeline architecture and ensure technical solutions align with business requirements.

Responsibilities

• Design, develop, test, and debug reliable data systems and machine learning models.
• Build and maintain ETL pipelines for large datasets using AWS services.
• Analyze and enhance existing systems to improve efficiency and performance.
• Collaborate with Business Systems Analysts to align technical solutions with business needs.
• Provide technical and functional guidance to project teams within your discipline.

Required Skills

• 7+ years of hands-on experience in data warehousing, data engineering, and machine learning.
• Proficiency in Python development, specifically with Spark or PySpark and API integration.
• Experience building ETL pipelines with AWS Glue, EMR, Kinesis, Kafka, or CloudWatch.
• Expertise in writing SQL queries and performance tuning in AWS Redshift, MS SQL Server, or Postgres.
• Proficiency with AWS services including Lambda, Event Bridge, Step Functions, SNS, SQS, and S3.
• Experience designing and building machine learning models and algorithms.
• Knowledge of machine learning, deep learning AMIs, and natural language processing (NLP) techniques.
• Understanding of IAM Roles and Policies.
• Bachelor's Degree.

Preferred Skills

• Experience integrating applications into existing business processes.

Key Skills

Education

Bachelor's Degree