Overview

·Provideengineering on modern, cloud-based data processing technology stack

·Builddata pipelines, data validation frameworks, job schedules with emphasis onautomation and scale

·Contributeto overall architecture, framework, and design patterns to store and processhigh data volumes

·Ensureproduct and technical features are delivered to spec and on-time

·Designand implement features in collaboration with product owners, reporting analysts/ data analysts, and business partners within an Agile / Scrum methodology

·Proactivelysupport product health by building solutions that are automated, scalable, andsustainable – be relentlessly focused on minimizing defects and technical debt

·Should be a good communicator,excellent team player, able to collaborate with remote team members over zoom,demonstrating great flexibility

Requirements

Qualifications

• Masters’ or Bachelors’ degree in Computer Science or a related field
• 6 years of experience in data engineering development
• 4 years of experience implementing scalable data architectures
• 3 years of experience in large-scale software development with emphasis on data analytics and high-volume data processing
• 3 years of experience with AWS and related services (e.g., EC2, S3, DynamoDB, Elasticsearch (DSL Queries), Kinesis Streams, SQS, SNS, Lambda, AppSync)
• Expert Experience in python is a hard requirement. Experience in other data-centric programming languages is a plus.
• 5 years of experience in database development using relational and non-relational database is preferred. SQL experience is preferred.
• Experience with CI/CD tools like Jenkins / Terraform as IAAS (infrastructure as a service)
• Experience with Docker. Deploying containerized solutions in AWS (ECS / EKS)