Big Data Engineering Manager/Lead, Trek 3 in Phoenix, Arizona | Careers at 9903 – Field (AZ)

LogMeIn
LogMeIn

Job Overview

Overview

Here at LogMeIn, we offer a broad portfolio of SaaS products that unlock the potential of the modern remote, in-office and hybrid workforces. We help people do their best work – whenever, wherever and, however. With millions of users across the globe, our portfolio includes some of the most recognized and popular software products in the world today, (Inc. bold360, GoToMeeting, GoToWebinar, LastPass, Rescue, etc.).

Currently, we are expanding the scope and scale of our global Data team. To support this growth, we’re searching for a Big Data Engineering Manager (Inc. lead-level, ‘hands-on’ development) to join our team.

In this role, you will report directly to our Senior Director of Data Engineering. You will focus on 2 primary objectives. One of those primary objectives will be to deliver high-quality data products to our Customer Engagement and Support (CES) and Care business teams. The other primary objective will be to build and lead a small Data Engineering team responsible for building, delivering and supporting those high-quality data products.

Responsibilities

  • Build, develop and lead a new Data Engineering team referred to as our Trek 3 team
  • Partner with our Talent Acquisition team to identify, screen/interview and hire a small team (2) of Data Engineers for Trek 3; following hiring best practices throughout every step of the interview and selection process
  • Effectively lead, manage and develop the Trek 3 team; including, all formal personnel management responsibilities
  • Contribute to the design, development, integration and support of data products utilizing modern, ‘hands-on’ and lead-level, Data Engineering technical skills and practices in an Agile/Scrum environment, (Please note: ‘hands-on’ development responsibilities do represent a significant component of this role)
  • Build credibility and trust with the Data Product Manager, and key stakeholders within our CES and Care organizations, through effective communications as well as demonstrated knowledge, expertise and actions
  • Collaborate with our Data Product Manager, and key stakeholders within our CES and Care organizations, to effectively identify, scope and deliver high-quality data product in a timely manner
  • Foster a positive Data Engineering and LogMeIn work culture through attitudes, actions and ongoing demonstrations of company core values

Qualifications

  • Bachelor’s degree in Computer Science required; Master’s degree preferred
  • 7+ years of relevant skills and career experiences in Big Data Engineering and Data Warehousing
  • 5+ years of hands-on experience writing complex, highly optimized SQL queries across large data sets
  • 2+ years of formal Engineering Team Lead and or small Team Management experience, (i.e. personnel management)
  • Demonstrated strengths in Data Modelling, ETL Development and Data Warehousing
  • Experience with AWS services including S3, EMR, Kinesis and RDS
  • Experience with Big Data stack of technologies, including Hadoop, HDFS, Hive, Spark, Pig, Presto, etc.
  • Knowledge of distributed systems as they pertain to data storage and computing
  • Exceptional problem solving and analytical skills
  • Knowledge of software engineering best practices across the development lifecycle; including, Agile methodologies, coding standards, code reviews, source management, build processes, testing and operations

LogMeIn Product Portfolio: GoToMeeting, GoToWebinar, Grasshopper, Join.me, GoToTraining, OpenVoice, Jive, Rescue, Bold360, GoToAssist Seeit, GoToAssist, Rescue Lens, LastPass, Pro, Central, GoToMyPC, (https://www.logmeininc.com/products)

Keywords: Agile, Architecture, AWS, BI, Big Data, Cloud, Computer Science, Data Modelling, Design, Develop, EMR, Engineer, ETL, EverGreen, Extract, Hadoop, HDFS, Hive, Infrastructure, Integration, Kinesis, Lead, LS, Manage, Mentor, Pig, Pipelines, Platform, Presto, Python, RDS, #RPJ, S3, SaaS, Scrum, Software, Spark, SQL, Transform, Warehouse

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