Samba - Data Engineer
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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) • 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 SQLExperience with data modeling, data lakes, and lakehouse architectures and a strong understanding of distributed systems and big data processing • Experience with Infrastructure as Code (Terraform) • Knowledge of CI/CD pipelines for data platforms • Experience working in Agile/Scrum environments • AWS, Databricks, or cloud data certifications • Experience working with data clean room environments, including implementation or collaboration within Snowflake, Databricks, or BigQuery ecosystems • Experience with streaming data pipelines (Kafka, Flink) • 230,000 zł - 380,000 zł a year
Responsibilities
• Build scalable data product architecture, capable of supporting both internal and external data consumers • Responsible for modernizing our 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 (Great Expectations or similar)Implement monitoring and anomaly detection systems for data quality, reliability and performance • 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
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