Senior Data Engineer – Python, Spark, AWSWe’re looking for a Senior Data Engineer to join a highly skilled team responsible for building a scalable, multitenant data platform that powers data ingestion, transformation, cataloging, and distribution for internal and external stakeholders. This role is central to designing robust data pipelines, integrating modern data lakehouse components, and supporting the company’s AWS-based infrastructure.🔧 What You’ll Do: Design and build scalable data ingestion pipelines in AWS Work extensively with Databricks, including Unity Catalog, streaming, Delta Lake, and data transformation tools Lead technical delivery and implementation of core platform components across raw, normalized, operational, and historical layers Collaborate with engineering managers and cross-functional teams across the US and Poland Drive technical excellence by improving team processes, architecture standards, and engineering best practices Support and consult with stakeholders to ensure successful delivery of data-driven solutions Contribute to the growth and maturity of the team’s cloud and data engineering capabilities ✅ What We’re Looking For: 5+ years of experience in Python and strong software engineering skills Solid knowledge of AWS cloud services and best practices Experience building scalable Spark pipelines in PySpark or Scala Practical experience with Spark Streaming for low-latency pipelines Familiarity with Delta Lake and modern data lakehouse architectures Hands-on experience with Kubernetes and container orchestration Experience with MongoDB and other NoSQL data stores Understanding of microservices and event-driven architecture Excellent communication skills and ability to work in a collaborative, global team Commitment to high standards of ethics, quality, and delivery 🌟 Nice to Have:Familiarity with Machine Learning, AI models, or Data Science workflows