Build and maintain scalable data services, pipelines and storage solutions for the feedback of unstructured application data for ML training and evaluation purposes.
Build and manage OLAP databases, ELTs and general data tooling for analytics, business decisions and products features.
Work closely with a team of frontend and backend engineers, product managers, and analysts.
Optimize data infrastructure to enhance the throughput, latency and reliability of the data system.
Investigate and correct issues identified through data operations monitors, tools, and reports.
Designs data integrations and data quality framework.

Requirements

5+ years of experience in Data Engineering or Backend Engineering with a focus on data systems.
Proficient in at least one general purpose programming language (e.g., Python, Java, Scala) and SQL (any variant)
Proficiency with at least one modern cloud provider (GCP, AWS, Azure) and accompanying data services
Experience in building systems that manage the ingest, transformation, and management of both structured and unstructured data types
Deep knowledge of modern data infrastructure best practices
Experience with distributed systems and different distributed processing frameworks
Experience with Terraform, Kubernetes, and containerization technologies.
Familiarity with deploying ML models at scale a bonus
Experience in building data products that are well-modeled, documented and easy to understand and maintain.
Ability to prioritize amidst changing priorities in a fast moving environment.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data EngineeringBackend EngineeringPythonJavaScalaSQLCloud ComputingData IngestionData TransformationData Management

Soft Skills

Team CollaborationProblem SolvingPrioritizationAdaptability