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Senior Data Engineer – Python, Spark, AWS
We’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
Net per month - B2B
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