Key Responsibilities

📍Design, build, and maintain large-scale batch and streaming data pipelines using Databricks and Spark (PySpark/Scala) 📍Develop and optimize data transformations leveraging Delta Lake and lakehouse architectures 📍Implement job scheduling, workflow orchestration, and performance tuning for scalable data processing 📍Write clean, maintainable, and well-documented Python and SQL code following best practices and version control standards 📍Manage distributed data storage formats, metadata, and performance optimization strategies

What Makes You a Great Fit

📍4–6+ years of experience in Data Engineering or Data Platform roles 📍Strong hands-on expertise in Databricks, Spark (PySpark/Scala), and Delta Lake 📍Proficiency in Python and SQL with deep understanding of distributed data systems 📍Experience building and maintaining scalable batch and streaming pipelines 📍Solid understanding of cloud-native data architectures across AWS, Azure, or GCP 📍Knowledge of data governance, security, access control, and compliance best practices 📍Experience with data modeling and data warehousing concepts 📍Familiarity with Django/Django REST Framework or similar API development frameworks is a plus

The future of finance is here — whether you’re interested in blockchain, cryptocurrency, or remote web3 jobs, there’s a perfect role waiting for you.