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. GoToMeeting, GoToWebinar, LastPass, GoToConnect, etc.).
We are expanding the scope and scale of our global Data team. To support this growth, we’re searching for a Senior Big Data Engineer to join our team.
Our feature stores are leveraged by Data Scientists and Data Analysts every day. These stores are the foundations of our Engagement Platform and Machine Learning Platform. These platforms enable intelligent targeting and utilize data to deliver contextually relevant experiences for customers via multiple channels, (e.g. Commerce, Product, Sales, Care) to drive conversion, retention, up-sales and cross-sales.
In this role, you will be collaborating with Data Scientists, Data Analysts, Software Engineers, Product Managers/Marketers, Executives and other key stakeholders around the world. You will have the opportunity to apply your senior-level knowledge, skills and experiences to help build the Data systems and platforms that unleash high-value business insights. Your efforts will have a direct impact on creating delightfully smart, personalized and revolutionary customer experiences.
- Partner with our Active Insights team to build an offline feature set for Data Analysis and Machine Learning model training
- Develop, deploy and maintain an online feature store for real-time data access in production systems
- Collaborate with Data Scientists, Data Analysts and Engineers to gather data requirements and model data as needed
- Apply your knowledge of technology options, technology platforms, design techniques and approaches across the data warehouse lifecycle to design a consolidated, standardized and integrated solution to address business requirements
- Ensure completeness and compatibility of the technical infrastructure required to support system performance, availability and architecture requirements
- Participate in architecture design and implementation of next generation BI solution
- Help build robust and scalable data integration (ETL) pipelines using AWS Services, EMR, Python, Pig and Spark
- Build and deliver high quality data architecture to support Business Analysts, Data Scientists and customer reporting needs
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
- Continually improve ongoing reporting and analysis processes; automating or simplifying self-service support for customers
- Bachelor’s degree in Computer Science required; Master’s degree preferred
- 2-5+ years of relevant experience in one or more of the following areas: Big Data Engineering, Data Warehouse, Business Intelligence or Business Analytics
- 2+ years of hands-on experience in writing complex, highly optimized SQL queries across large data sets
- Demonstrated strength 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
- 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, EMR, Engineer, ETL, EverGreen, Extract, Hadoop, HDFS, Hive, Infrastructure, Integration, Kinesis, LS, Pig, Pipelines, Platform, Presto, Python, RDS, RPJ, S3, SaaS, Software, Spark, SQL, Transform, Warehouse
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