Data Engineer at sambatv

sambatv

Warsaw·13h ago

Mid LevelInternshipPythonAWSKubernetesTerraformREST APIMachine LearningAgileScrumCI/CDAI

Salary Range

$102,000 - $138,000 /year

Estimated

This salary is estimated based on similar roles. The actual salary may vary.

About the Role

We are seeking a skilled Data Engineer to strengthen our data platform team at Samba TV. Our team is responsible for building and maintaining the data platform that powers the entire organization, from ingestion to analytics and reporting.

Key Responsibilities

→Build scalable data product architecture to support both internal and external data consumers
→Modernize data frameworks and integrations with Databricks and BigQuery
→Upgrade and reduce toil for developers on Apache Airflow
→Develop and optimize data transformations using Apache Spark (PySpark/Scala)
→Build procedures and guidelines to help teams operate with data
→Identify bottlenecks in our development lifecycle and find solutions to improve them
→Drive innovation throughout the tech org by evangelizing and educating teams on best practices and new technologies
→Work directly with our data teams and FinOps teams to drive efforts that span across teams
→Implement data governance, access control, and auditing using Databricks Unity Catalog
→Build and integrate automated, reusable data validation suites using data quality frameworks
→Develop and manage REST APIs to support secure data access, automation, and integration
→Collaborate with data scientists, analysts, and software engineers to deliver governed, reusable data assets
→Implement monitoring, logging, and alerting for data workflows
→Optimize cost and performance of cloud-based data infrastructure

Requirements

✓Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
✓5+ years of experience in data engineering or a related role
✓Strong hands-on experience with Databricks, Apache Spark and BigQuery or Snowflake
✓Proven experience with Modern table formats such as Delta Lake and Iceberg
✓A deep understanding of the data lifecycle and how teams operate with data
✓Hands-on experience implementing data governance and metadata management using Databricks Unity Catalog
✓Experience managing and extending Apache Airflow (custom operators, plugins, infrastructure)
✓Experience with Kubernetes
✓Solid experience with AWS cloud services, especially S3 and data-related services
✓Experience with data validation and data quality principles and working with SLA systems
✓Proficiency in Python and SQL
✓Experience with data modeling, data lakes, and lakehouse architectures and a strong understanding of distributed systems and big data processing