Big Data Engineer
665 Clyde Avenue Mountain View, CA 94043
ektello is on the hunt for a Big Data Engineer for one of our top professional electronic corporations in the world. Our client boasts an impressive portfolio of digital products including home and smart appliance technology, mobile phones, virtual reality, as well as computing and gaming.
In today’ s fast-evolving technology world, one aspect remains common – reliance on data to drive the next wave of innovation. Strategic Analytics is our client' s Center-of-Excellence for driving the adoption of data-driven decision making and product development across the company. The team’ s core focus is developing best-in-class solutions that provide our client' s marketing and service organizations with a 360-degree view of their customers.
Strategic Analytics is powering a paradigm shift for our client and the global industry. We are looking for highly technical team members who are passionate about data, have the rigor needed to solve billion dollar problems, and possess an innate entrepreneurial spirit to explore the uncharted. Strategic Analytics combines the engineering backbone of a best-in-class Big Data Platform with the analytic expertise of advanced mining and predictive modeling.
Big Data Engineers serve as the backbone of the Strategic Analytics organization, ensuring both the reliability and applicability of the team’ s data products to the entire organization. They have extensive experience with ETL design, coding, and testing patterns as well as engineering software platforms and large-scale data infrastructures. Big Data Engineers have the capability to architect highly scalable end-to-end pipeline using different open source tools, including building high-performance algorithms.
Big Data Engineers understand how to apply technologies to solve big data problems with expert knowledge in programming languages like Java, Python, Linux, PHP, Hive, Impala, and Spark. Extensive experience working with both 1) big data platforms and 2) real-time/streaming delivery of data is essential.
Big data engineers implement complex big data projects with a focus on collecting, parsing, managing, analyzing, and visualizing large sets of data to turn information into actionable deliverables across customer-facing platforms. They have a strong aptitude to decide on the needed hardware and software design and can guide the development of such plans through both proof of concepts and complete implementations.
• Tune Hadoop solutions to improve performance and end-user experience
• Proficient in designing efficient and robust data workflows
• Documenting requirements as well as resolve conflicts or ambiguities
• Experience working in teams and collaborate with others to clarify requirements
• Strong coordination and project management skills to handle complex projects
• Excellent oral and written communication skills
• Translate complex functional and technical requirements into detailed design.
• Design for now and future success
• Hadoop technical development and implementation.
• Loading from disparate data sets by leveraging various big data technology, e.g., Kafka
• Pre-processing using Hive, Impala, Spark, and Pig
• Design and implement data modeling
• Maintain security and data privacy in an environment secured using Kerberos and LDAP
• High-speed querying using in-memory technologies such as Spark.
• Following and contributing best engineering practice for source control, release management, deployment, etc
• Production support, job scheduling/monitoring, ETL data quality, data freshness reporting
• 5-8 years of Python or Java/J2EE development experience
• 3+ years of demonstrated technical proficiency with Hadoop and big data projects
• 5-8 years of demonstrated experience and success in data modeling
• Fluent in writing shell scripts [bash, korn]
• Write high-performance, reliable and maintainable code.
• Ability to write MapReduce jobs
• Ability to set up, maintain, and implement Kafka topics and processes
• Understanding and implementation of Flume processes
• Good knowledge of database structures, theories, principles, and practices.
• Understand how to develop code in an environment secured using a local KDC and OpenLDAP.
• Familiarity with and implementation knowledge of loading data using Sqoop.
• Knowledge and ability to implement workflow/schedulers within Oozie
• Experience working with AWS components [EC2, S3, SNS, SQS]
• Analytical and problem-solving skills applied to Big Data domain
• Proven understanding and hands-on experience with Hadoop, Hive, Pig, Impala, and Spark
• Good aptitude in multi-threading and concurrency concepts.
• B.S. or M.S. in Computer Science or Engineering