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Data/BigData Solutions Architect

Data/BigData Solutions Architect

Full Time

9 am - 5 pm

Job Description

You should be able to help us enhance our data capabilities and create a competitive advantage. Your passion for data architecture principles is infectious and inspires the teams to engage, inspect, adapt, and continuously improve. You are highly organized with positive energy that fosters a great team dynamic and the strong interactions that define a winning team. This position requires active participation in the modeling techniques for conceptual, logical and physical data models.

A Big Data Solutions Architect generally should have a lot of experience gained in normal solutions architecture before making the move to big data solutions. 10-15 years of working experience is very common for this position. Obviously, he or she needs to have experience with the major big data solutions like Hadoop, MapReduce, Hive, HBase, MongoDB, Cassandra. Quite often they also need to have experience in big data solutions like Impala, Oozie, Mahout, Flume, ZooKeeper and/or Sqoop.

In addition to big data solutions, a big data solutions architect needs to have a firm understanding of major programming/scripting languages like Java, Linux, PHP, Ruby, Phyton and/or R. As well as have experience in working with ETL tools such as Informatica, Talend and/or Pentaho.  He or she should have experience in designing solutions for multiple large data warehouses with a good understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS and/or knowledge on NoSQL platforms.

Job Responsibilities

  • Architecting highly-scalable, distributed enterprise data solutions with focus on big data platforms and enterprise data lake for reporting & analytics, and particular focus on Cloud-based data platforms
  • Designing and developing highly scalable and flexible data platform solutions
  • Designing and documenting architecture at multiple levels (high-level to detailed) and across multiple views (conceptual, logical, physical, data flow and sequence diagrams)
  • Providing active “hands-on” architectural guidance and leadership through the entire lifecycle of development projects

Qualifications

  • Proactive: Acts without being told what to do. Brings new ideas to the company.
  • Bachelor’s degree in Data Science or Data engineering
  • 5+ years of data experience
  • Persistence: Demonstrates tenacity and willingness to go the distance to get something done.
  • Attention to Detail: Does not let important details slip through the cracks or derail a project.

Other Benefits

  • Demonstrated ability to assess current source systems and create an integrated multi-domain model.
  • Experience with Data Modelling tools like Erwin is required

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