Data Engineer

Description

Welcome to Zesty, a dynamic startup at the forefront of cloud optimization innovation!

Zesty’s Mission

Zesty is a startup company specializing in automated optimization solutions, aiming to help organizations reduce costs and enhance operational efficiency. The company offers a range of products designed for DevOps and FinOps teams responsible for managing cloud usage within organizations.

Position Overview

We are looking for a hands-on Data Engineer to join Zesty’s engineering team and take ownership of core data processes within one of our product teams.

You will design and maintain reliable ETL pipelines, connect to external data sources, and help build scalable data foundations for product features, analytics, and AI-driven capabilities. This is a great opportunity to own meaningful data processes end-to-end and work closely with product, engineering, and data stakeholders.

Your Ownership Will Include

• Design, build, and maintain end-to-end ETL pipelines for production use.
• Work with large-scale cloud usage data from different sources and formats.
• Build data flows using Apache Spark and Databricks or similar technologies.
• Structure data using Data Lake / Lakehouse concepts, including Bronze, Silver, and Gold layers.
• Integrate with external APIs and data sources.
• Prepare and model data for product features, analytics, and AI-related capabilities.
• Ensure data quality, reliability, and observability across pipelines.
• Collaborate closely with backend engineers, data analysts, and product stakeholders.
  
  

• 3+ years of experience as a Data Engineer or in a similar data development role.
• Proven experience building production ETL pipelines end-to-end.
• Hands-on experience with Apache Spark, preferably PySpark or Scala.
• Experience with Databricks or a similar data processing platform.
• Strong understanding of Data Lake / Lakehouse architecture and data modeling.
• Experience integrating with external APIs and multiple data sources.
• Strong programming skills in Python, Scala, Java, or a similar language.
• Understanding of data quality, monitoring, validation, and pipeline reliability.
• Ability to work independently, take ownership, and collaborate effectively.
• Good communication skills in English.
  
  

• Experience with AWS data sources or cloud billing / usage data.
• Experience with Delta Lake, partitioning, schema evolution, and Bronze/Silver/Gold methodologies.
• Familiarity with orchestration tools such as Databricks Workflows, Airflow, or similar.
• Experience with AI-related data preparation or ML/AI data workflows.
• Experience working in a SaaS or cloud infrastructure company.
  
  

• Diversity & Inclusion - Be yourself! We welcome employees from all backgrounds and have created a workplace where everyone can feel empowered.
• Transparency - We share our success stories, failures, processes, numbers, and everything in between. If you want to know something that wasn't shared with you – just ask!
• One Team - We genuinely trust each other which enables us to act as one team working together toward the same mission. All team members are equally important
• Open Communication & Feedback - When facing challenges, we always look for fresh ideas and ways to overcome them and We embrace constructive feedback that can and should be given to anyone
• Ego is out at the door - Ego obscures and disrupts everything: the planning process, the ability to take good advice, and the ability to accept constructive feedback. We operate with a high degree of humility