Design, build, and optimize high-scale data infrastructure and platforms.
•Join a cross-functional team of Software Engineers and Data Engineers working closely with data scientists and other engineering teams.
•Key Responsibilities Build and maintain high-performance, scalable data systems and architectures.
•Design and develop robust ETL/ELT pipelines for both batch and streaming data.
•Deploy, manage, and monitor cloud-based data infrastructure with a heavy emphasis on automation and reliability.
•Support Data Scientists by streamlining, automating, and deploying machine learning models.
•Improve and maintain data quality, data modeling, and governance standards.
•Requirements Solid background in Software Engineering with practical experience managing and processing "Big Data" within data lakes and data warehouses.
•Hands-on experience creating, deploying, and maintaining cloud infrastructure using Terraform.
•Strong proficiency in Python and SQL, alongside deep comfort with core software development principles.
•Practical experience in one or more backend programming languages (Java, Scala, Go, Rust, C++, etc.).
•Experience working with major data warehouse/lake platforms (e.g., Databricks, Snowflake, AWS, Azure, or GCP) and designing complex DAGs in Airflow.
•Experience with data streaming tools and frameworks such as Spark Streaming and Kafka.
•Exposure to, or strong interest in, MLOps (Machine Learning operations) and building/comfort with AI agentic workflows.
•Solid understanding of data modeling, cataloging, governance, and quality monitoring.
•Experience developing scalable data architectures in accordance with global compliance standards (GDPR, CCPA, LGPD, or PDPA).