Customer Solutions Engineer

Customer Solution Engineers are the primary technical resource for the field sales & post-sales delivery teams and are responsible for actively guiding and driving our product value & adoption, playing the role of key technical advisor and product advocate. The Customer Solution Engineer must be able to identify and provide reliable solutions to assure customer success through all stages of the sales & delivery process.

 

About you

  • Master’s in Computer Science or equivalent
  • 4+ years of experience in Java, Python, Scala, Spark.
  • 3+ years of experience in RDBMS and NoSQL.
  • 3+ years of implementing complex data pipelines in one of the major Cloud providers.
  • Cloud Engineering/Architect Certification from one of the Cloud Service Providers.
  • Skilled in data management, data warehousing, data orchestration, and data integration technologies.
  • Self-motivated and organized to learn and apply new technologies to craft solutions meeting customer needs.
  • Understand and enjoy working with big data and data technologies from databases, ETL, data governance, and business intelligence tools.
  • Thrive in an environment where you can take ownership of a variety of projects and see them through to completion.
  • Can work independently in a start-up environment.
  • A builder of solutions based on a true understanding of customer requirements demonstrating feasibility of the application, often requiring rapid prototyping and/or product solution walk through to customers.

Nice to Have

  • Experience with industry leading data integration tools such as Informatica, Talend, Fivetran, Matillion, Azure Data Factory, and AWS Glue is a plus.
  • Knowledge of Kubernetes fundamentals.

Responsibilities

  • Be the product expert.
  • Provide Subject Matter Expertise to various stakeholders regarding the product and various Big Data/Data Engineering stack
  •  Building and implementing scalable centralized data engineering solutions on either On-Prem, Cloud or Hybrid infrastructures are highly complex and relies on various other technologies like Hadoop, Spark, Hive, etc.
  • Identify and Improve end to end feature velocity for data extraction, transformation and orchestration to optimize enterprise data pipelines/workflows.
  • Build Internal/External Solutions that translate into cost saving solutions for both internal and external teams.
  • Develop tools and features to aid operations and maintenance.
  • Maintaining and understanding of relevant industry trends and current knowledge of the big data ecosystems deployed by various large enterprises.
  • Perform technical/product training for salespeople, estimators, and engineers at targeted accounts.
  • Resolve customer issues or difficulties in a manner that is consistent with the company mission, values, and financial objectives.

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