Description

You will design, develop, and maintain data systems and machine learning models, owning the ETL pipeline architecture.

This role is on-site.

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.

Preferred Skills

• Experience integrating applications into existing business processes.

Bachelor's Degree required.

Key Skills

Education

Bachelor's Degree