Data Infrastructure Engineer

Melio
·
Posted: 
March 19, 2023
·
Remote
Job Commitment
Full-time
Job Commitment
Mid Level
Job Function
Dev & Engineering
Salary
N/A
Job Commitment
Full-time
Experience Level
Mid Level
Workplace Type
Remote
Job Function

This job is closed

We regret to inform you that the job you were interested in has now been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.

About the position

We are seeking an experienced Senior Engineer for our Data Infrastructure team to design, implement, and maintain various data services to enable internal teams to process, store, orchestrate, and consume data effectively. The ideal candidate will have a strong background in data and backend engineering and a track record of designing and implementing scalable data solutions. The Data Infrastructure Engineer will collaborate closely with software engineers, data scientists, data engineers, and other stakeholders to understand requirements, design solutions, and implement data-related features and functionalities. The role involves designing and building data storage, processing, and access systems that are scalable, reliable, and secure, as well as designing and implementing data pipelines, data warehousing, and data architecture to support our business needs.

Responsibilities

  • Design and build data storage, processing, and access systems that are scalable, reliable, and secure.
  • Design and implement data pipelines, data warehousing and data architecture to support business needs.
  • Design and implement CI/CD processes for training, releasing, serving and monitoring machine learning models.
  • Collaborate with other teams to integrate data and machine learning models into products and services.
  • Ensure that data systems are compliant with regulatory requirements and industry best practices.

Requirements

  • 5+ years of experience in data and backend engineering.
  • Strong knowledge of data architecture, data schematizing and ETL processes.
  • Experience with cloud-based data infrastructure, such as AWS, GCP or Azure.
  • Experience with SQL and NoSQL databases.
  • Experience with Data Warehouse technologies such as Snowflake and BigQuery.
  • Experience working with Python.
  • Excellent communication and collaboration skills.
  • Experience working with Typescript is a plus.
  • Experience building infrastructure for Machine Learning is a big plus.
  • Experience administering and managing Apache Spark clusters is a plus.
  • Experience with streaming technologies such as Apache Kafka and Amazon Kinesis is a big plus.
  • Experience working with serverless products such as AWS Lambda is a plus.

Benefits

Job Application Resources

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