Data Engineer

Required Data Engineer
About The Position
A modern, full-stack observability platform transforming how businesses process and understand their data. Our unique architecture powers in-stream analytics without reliance on expensive indexing or hot storage. We specialize in comprehensive monitoring of logs, metrics, trace and security events with features such as APM, RUM, SIEM, Kubernetes monitoring and more, all enhancing operational efficiency and reducing observability spend by up to 70%.
About the role:
As a Data Engineer, you will be responsible for defining, developing and managing curated datasets, key business metrics and reporting across functional units. You will architect, implement and manage data models, ELTs and ETLs that will enable product, engineering and business teams access consistent data, in near real time, across the ecosystem and services. You are a self-starter and you are comfortable working cross-functionally with other teams across.
What Youll Do:
Partner with business stakeholders, upstream infrastructure platform engineering teams and downstream data consumers to understand data and translate business requirements into technical design of building scalable data pipelines.
Develop and take ownership of BI data pipelines and centralized data warehouses with trustworthy curated datasets and standardized metrics and business definitions to empower data access and self-service.
Provide the direction of our data engineering and architecture. Determine the right tools for the right jobs.
Institute data engineering best practices (i.e. dimensional modeling, ETL/ELT pipeline, large scale distributed ETL/ELT pipelines) to enable large-scale machine learning.
Create and maintain analytics data pipelines that generates data + insight to power business decision making.
Provide feedback to Product and Engineering teams on new and upcoming features.