
Chief Data Architect
2 days ago
We are seeking a highly skilled Senior Data Engineer to join our team and contribute to the development of our data foundation.
Build and optimize large-scale data pipelines using PySpark and Databricks.
Automate and cost-optimize AWS data infrastructure.
Collaborate with data science and analytics teams to productionize models and build data products for campaign analysis.
Ensure data quality and privacy by implementing automated monitoring and rapid de-anonymization for secure datasets.
Develop core infrastructure including golden tables, reports, and dashboards.
Lead foundational projects such as automating and re-architecting the core data prep platform.
Core Qualifications:
5+ years of professional experience in data engineering; 7+ years with demonstrated technical leadership.
Advanced proficiency in Python and extensive hands-on experience with PySpark.
Practical experience with the Databricks platform and strong understanding of how to optimize Spark jobs for performance and cost.
Ability to write, debug, and optimize complex SQL queries.
Strong experience with AWS cloud services, particularly S3 for data storage and SQS/SNS for messaging, serverless functions.
Solid understanding of Data Lake and Data Warehouse architectures and design principles.
Experience with workflow orchestration tools like Apache Airflow and building/maintaining CI/CD pipelines.
Foundational knowledge of Docker and Kubernetes.
Professional fluency in English.
Nice-to-Have Qualifications:
Experience with geospatial libraries and tools.
Experience with Infrastructure as Code using Terraform.
Familiarity with columnar databases.
Experience with monitoring stacks.
Proficiency with Git and collaborative workflows.
This is an excellent opportunity for a senior data engineer to take on a leadership role and make a significant impact on our data foundation. If you have a passion for building scalable data systems and working with a talented team, we encourage you to apply.
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