Description

Job Responsibilities:

  • Assist in Presales and client problem definition phase of an Azure data engagement. Work closely with the presales engineers to design the best-in-class Azure data solution and scoping to satisfy client requirements.
  • Ability to handle multiple client engagements in different stages of the implementation lifecycle.
  • Provide hands-on guidance, mentoring, and validation for the project teams during the implementation of the client engagement.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Required Skills:

  • Demonstrated work experience with handling streaming/time-series data using AWS Kinesis/AWS-managed Kafka
  • ETL development experience in SQL, Python, Java/Scala
  • Implementation experience of self-service data layer using data mesh/ data fabric or other architectures for data sharing and governance
  • Familiarity with Lakehouse architectures
  • Experience with other dashboarding solutions like Tableau, Qlik, and/or similar programs is a plus.
  • Excellent verbal and written communication skills to effectively interact with both technical and executive stakeholders on client engagements.

Additional Desired Skills:

  • Working experience with Snowflake or Databricks is a plus
  • Experience on Azure and GCP data stack is definitely a plus

Education and Experience:

  • Bachelor's degree or equivalent experience and/or military experience
  • Over all 10+ years of experience in Data Engineering
  • 10+ years of advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

5+ Strong work experience on AWS Data Analytics stack - EMR, Redshift, Kinesis/managed

Key Skills
Education

Bachelor's degree

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