Data Engineer (Spark) – Remote

About the role

We are looking for a Data Engineer specialized in Apache Spark to design and build large‑scale data pipelines. You will connect raw data sources to analytical insights, ensuring high performance and scalability across cloud environments.

Key responsibilities

• Design and develop robust data pipelines using Python and PySpark to process massive datasets.
• Optimize Spark jobs by tuning internals, improving performance and controlling costs.
• Implement scalable storage solutions with Delta Lake or Apache Iceberg for reliable data management.
• Orchestrate complex workflows with Airflow to guarantee timely and accurate data delivery.
• Build and maintain data processing infrastructure on AWS, Azure, or GCP, and write complex SQL queries for transformation and validation.

Required profile

• 4+ years of experience in Data Engineering or Software Engineering.
• Proven expertise in building large‑scale batch and streaming pipelines using Apache Spark and Python.
• Hands‑on experience with Spark internals, PySpark, and Delta Lake or Apache Iceberg.
• Proficiency in SQL and workflow orchestration tools such as Airflow.
• Practical experience with cloud data platforms (AWS, Azure, or GCP) and advanced English proficiency.

Required skills

• Python
• PySpark / Apache Spark
• Delta Lake
• Apache Iceberg
• SQL
• Airflow
• AWS
• Azure
• GCP

What we offer

• 100% remote work from anywhere.
• Competitive compensation paid in USD or local currency.
• Provided hardware and software setup for home office.
• Flexible hours to create your own schedule.
• Paid parental leave, vacations, national holidays, and a multicultural environment with mentorship and growth opportunities.