Description

You will design and own end-to-end data engineering solutions for large-scale batch and streaming systems.

This role is on-site.

Responsibilities

• Design scalable data models and high-performance data lakes optimized for storage and retrieval.
• Build and maintain efficient ELT/ETL pipelines using Spark and Airflow or similar schedulers.
• Partner with product engineers and data scientists to define and prioritize business data requirements.
• Implement rigorous data quality frameworks to ensure accuracy, freshness, and trust.
• Mentor junior engineers and champion automated CI/CD deployments using Bitbucket and Git.

Required Skills

• 8+ years of professional experience as a Data Engineer or in a similar role.
• Experience building scalable data pipelines in Spark with Airflow or similar scheduling tools.
• Proficiency with Databricks and its APIs.
• Experience with modern databases (Redshift, DynamoDB, MongoDB, Postgres) and data lakes.
• Proficient in Python or Scala with strong SQL skills.
• Experience working with large-scale, high-performance data processing systems (batch and streaming).

Preferred Skills

• Experience in SaaS companies.
• Some experience with Machine Learning.
• Committed code to open source projects.

Key Skills

Education

Bachelor’s degree