Data Engineer strengthening data platform team at Samba TV to improve data analytics and reporting capabilities. Building on AWS, Databricks, BigQuery, and Snowflake technology.
Responsibilities
Build scalable data product architecture
Responsible for modernizing 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
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
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