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Samba

Posted 3 months ago

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Data Engineer

WarsawHybridFull-time

AI Summary

Data Engineer builds and maintains the data platform, enabling ingestion, analytics and reporting while working with AWS, Databricks, BigQuery and Snowflake to support data-driven decisions.

About this role

Samba is an AI-powered media intelligence company on a mission to give marketers the complete picture of their audiences. Our AI indexes media consumption across millions of smart TVs and 2.5 billion web pages, combining that data with third-party signals through the Samba Knowledge Graph, a map of the real interests, behaviors, and purchase intent of 1.5 billion user profiles globally. Brands, agencies, publishers, and platforms use Samba to make smarter decisions across every stage of the marketing funnel.

We are seeking a skilled Data Engineer to strengthen our data platform team. Our team is tasked with building and maintaining the data platform that powers the entire organization; from ingestion to analytics and reporting; from valuable viewership and contextual datasets to scalable applications that enable data-driven decision making. While our organization is hybrid, you'll be building mostly on AWS, Databricks, BigQuery and Snowflake technology. The ideal candidate will have strong experience in cloud-based data engineering, distributed data processing, and data governance and metadata management to support analytics, reporting, and machine learning use cases.

What You'll Do

  • 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
  • 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

    • Who You Are

  • Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
  • 2+ 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 SQLExperience with data modeling, data lakes, and lakehouse architectures and a strong understanding of distributed systems and big data processing

    • Skills

    AirflowAlertingApache AirflowApache SparkAWS S3BigQueryDatabricksDatabricks Unity CatalogData GovernanceData LakesData ModelingData QualityData ValidationDelta LakeGreat ExpectationsIcebergKubernetesLakehouseLoggingMetadata ManagementMonitoringPySparkPythonREST APIScalaSLA SystemsSnowflakeSQL

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