Principal Big Data Engineer - SaaS-based B2B Marketing Technology

San Francisco, CA

Posted: 08/15/2017 Industry: Big Data Engineer Job Number: 22908

Job Description

Category : Big Data Engineer
Location/City : CA - San Francisco
Area Code : 415
Job Type : 1: Full Time
Country/Locale : USA
Id : 22908

#22908 Principal Big Data Engineer - SaaS-based B2B Marketing TechnologyLocation: San FranciscoCompany
What do industry leaders like Adobe, American Express, Box, and SAP have in common? They all use our client ?'s solutions to power their targeted business-to-business (B2B) marketing efforts. With a roster of loyal, blue-chip customers that ?'s growing every day, they re in a phase of pre-IPO growth and building the team that will take them to the next level, which includes moving past legacy to create new core technologies with a focus on AI, ML & NLP/NLU. If you thrive on innovation and working with the best in industry, you re probably a good fit.

Our client has built a group of talented individuals with deep expertise in the domain area of business applications and building large complex systems with simple user interfaces. They also have deep expertise in big data technology such as IR, NLP, and large graphs and utilize the best technology to provide innovative and novel products to frustrated end-users in the enterprise.

As the Principal Data Engineer you will be responsible for scaling our machine learning pipeline, including requirements, architecture, design & development, quality assurance, deployment and operations. You will establish the ins and outs of building a highly available, scalable, distributed, and robust system that uses all the modern cloud computing paradigms, techniques and tools.To apply for the role, you should possess strong analytical, design, and problem diagnosis skills. You like thinking outside the box ? , are not afraid of ambiguity, get excited about difficult challenges, and are a motivated self-starter. You are a strong team player and thrive in a startup environment where flexibility is essential and delivering rock solid, customer focused solutions is paramount.Responsibilities:
- Core responsibilities will be to help scale large scale machine learning models.
- Own and drive processing of hundreds of terabytes of unstructured and structured data.
- Provide leadership to the data science and engineering teams in terms of big data processing.
- Develop the blueprint required to scale systems across dozens and hundreds of nodes.
- Enable machine learning systems to become more real-time in terms of decisions but also large scale data ingestion.
- Be a thought leader externally representing our company in conferences on AI and Big Data.
- Designing fault-tolerance, highly distributed, and robust systems.What are the minimum qualifications?
- Masters in Computer Science and/or 5+ years experience.
- Computer Science maestro in algorithms, data structures, especially distributed computing and graphs.
- Must have deep experience in multiple big data technologies, including Hadoop, MapReduce, Storm, Spark, Cassandra, Redshift, MongoDB, Athena, Kinesis etc.
- Experience working with terabyte level, real-time datasets.
- Deep experience with Java, C++, Python, and MySQL including relationship design.
- Knowledge of task management systems such as Celery, Amazon SimpleQueue, Kafka, and/or Kinesis.
- Basic understanding of machine learning and experience working with libraries such as SKLearn and Weka. You will be working with ML and understanding of general concepts is important.
- Ideally you are looking to grow your expertise in data science.
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.

Contact:Jon Piggins / Redfish TechnologyExecutive Recruiter, IT Sales & MarketingO: 208-788-8260E: jon[at]redfishtech[dot]comL: www.redfishtech.comRedfish Technology Building Growth-Mode Tech Companies with Hand-Picked Talent.

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