As a team member, you will be evolving and optimizing our data and data pipeline architecture, as well as, optimizing data flow and collection for cross functional teams. You are an expert data pipeline builder and data wrangler who enjoys optimizing data systems and evolving them. The Data Architect will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data and models devOps (dataOps) architecture is consistent throughout ongoing projects. You are self-directed and comfortable supporting the dataOps needs of multiple teams, systems and products. You will also be responsible for integrating them with the architecture used across the company. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s dataOps architecture to support our existing and next generation of MI-driven products and solutions initiatives

Responsibilities:

  • Create and maintain optimal data and model dataOps pipeline architecture
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and cloud-based ‘big data’ technologies from AWS, Azure and others.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data- related technical issues and support their data infrastructure needs.
  • Keep data separated and secure across national boundaries through multiple data centers and strategic customers/partners.
  • Create tool-chains for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and machine learning experts to strive for greater functionality in our data and model life cycle management systems.
  • Support dataOps competence build-up in the organization.

Requirements:

  • BS, MS or PhD degree in Computer Science, Informatics, Information Systems or another related field.
  • At least 3 years experience using the following software/tools:
  • Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with Data and Model pipeline and workflow management tools: Azkaban, Luigi, Airflow, Dataiku, etc.
  • Experience with stream-processing systems: Storm, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
  • You have advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of other databases/date-sources.
  • You have experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and seek opportunities for improvement.
  • You have strong analytic skills related to working with unstructured datasets.
  • You have built processes supporting data transformation, data structures, metadata, dependency and workload management.
  • Working knowledge of message queuing, stream processing, and highly sca

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