Senior Data Engineer

Unlock Employer New York, NY Full Time Live

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The most exciting part is the enormous potential for personal and professional growth. We are always seeking new and better tools to help us meet challenges such as adopting proven open-source technologies to make our data infrastructure more nimble, scalable and robust. Some of the cutting edge technologies we have recently implemented are Kafka, Spark Streaming, Docker and Mesos. 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, Vertica, Spark Streaming and Mesos 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, Vertica, RDBMS Ingest, validate and process internal & third party data Create, maintain and monitor data flows in Hive, SQL and Vertica for consistency, accuracy and lag time Maintain and enhance framework for jobs(primarily aggregate jobs in Hive) Create different consumers for data in Kafka such as flafka for Hadoop, flume for Vertica and Spark Streaming for near time aggregation Train Developers/Analysts on tools to pull data Tool evaluation/selection/implementation Backups/Retention/High Availability/Capacity Planning Disaster Recovery- We have all our core data services in another Data Center for complete business continuity 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: Chronos - 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 Marathon – cluster wide init for Docker Containers Mesos - Distributed cluster resource manager Spark Streaming - Near time aggregation SQL Server - Reliable OLTP RDBMS Sqoop - Import/Export data to RDBMS Vertica - fast parallel data warehouse 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 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 24x7 on-call rotation read more