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Senior Data Engineer

This is a Contract position in New York City, NY posted November 21, 2020.

Data Engineering team plays a key role in our technology company that?s experiencing exponential growth. Our data pipeline processes over 80 billion impressions a day (> 20TB of data, 220 TB uncompressed). This data is used to generate reports, update budgets, and drive our optimization engines. We do all this while running against extremely tight SLAs and provide stats and reports as close to real-time as possible.

What you’ll be doing:
? Design, build and maintain reliable and scalable enterprise level distributed transactional data processing systems for scaling the existing business and supporting new business initiatives
? Optimize jobs to utilize Kafka, Hadoop, Presto, Spark Streaming and Kubernetes resources in the most efficient way
? Monitor and provide transparency into data quality across systems (accuracy, consistency, completeness, etc)
? Increase accessibility and effectiveness of data (work with analysts, data scientists, and developers to build/deploy tools and datasets that fit their use cases)
? Collaborate within a small team with diverse technology backgrounds
? Provide mentorship and guidance to junior team members

Team Responsibilities:
? Installation, upkeep, maintenance and monitoring of Kafka, Hadoop, Presto, RDBMS
? Ingest, validate and process internal & third party data
? Create, maintain and monitor data flows in Hive, SQL and Presto for consistency, accuracy and lag time
? Maintain and enhance framework for jobs(primarily aggregate jobs in Hive)
? Create different consumers for data in Kafka using Spark Streaming for near time aggregation
? Train Developers/Analysts on tools to pull data
? Tool evaluation/selection/implementation
? Backups/Retention/High Availability/Capacity Planning
? Review/Approval – DDL for database, Hive Framework jobs and Spark Streaming to make sure they meet our standards
? 24*7 On call rotation for Production support

Technologies We Use:
? Airflow – for job scheduling
? Docker – Packaged container image with all dependencies
? Graphite/Beacon – for monitoring data flows
? Hive – SQL data warehouse layer for data in HDFS
? Impala- faster SQL layer on top of Hive
? Kafka- distributed commit log storage
? Kubernetes – Distributed cluster resource manager
? Presto – fast parallel data warehouse and data federation layer
? Spark Streaming – Near time aggregation
? SQL Server – Reliable OLTP RDBMS
? Sqoop – Import/Export data to RDBMS

Required Skills:
? BA/BS degree in Computer science or related field
? 5+ years of software engineering experience
? Knowledge and exposure to distributed production systems i.e Hadoop is a huge plus
? Knowledge and exposure to Cloud migration is a plus
? Proficiency in Linux
? Fluency in Python, Experience in Scala/Java is a huge plus
? Strong understanding of RDBMS, SQL;
? Passion for engineering and computer science around data
? Willingness to participate in 24×7 on-call rotation