AWS Data Engineer AWS Data Engineer …

Cognizant
in Brussels, Bruxelles-Capitale, Belgium
Permanent, Full time
Be the first to apply
Competitive
Cognizant
in Brussels, Bruxelles-Capitale, Belgium
Permanent, Full time
Be the first to apply
Competitive
Cognizant
AWS Data Engineer
Module lead(Depends on the project)

Qualification:

Bachelors in science , engineering or equivalent Responsibility:

Requirement Understanding and Analysis:

  • Review the raw requirements to understand the key outcomes expected by the client.
  • Identify data source and conduct data profiling to understand data and its quality.
  • Create a logic that needs to be incorporated in the architecture to ensure the data meets the requirements.
  • Create POC to conduct the feasibility of the requirement, as required.
Data Discovery & Profiling:

  • Post signoff, design basic queries to analyze the existing data.
  • Share sample data with the client to give a snapshot of the expected outcome.
  • Create a low level design document capturing SQL queries to achieve the target stage.
  • Share the document with the ETL team.
  • Conduct system integration testing during data migration from the source to the target state to ensure the requirements are met.
  • Conduct the root cause analysis of the issue to identify the solutions to resolve it.
  • Conduct testing to ensure the issue has been resolved.
  • In case of data issues, report it to the source team to fix the data.
  • If data is corrupted during migration, identify ways to cleanup the data.
  • Generate reports to fix the issues as required.
  • Understand the impact on data based on the release schedule.
  • Based on the understanding of the legacy system, provide inputs to the data modeler to map the attributes to the fields.
  • Share the data mapping documents with the data modeling team.
  • Support data modeling team to understand the data / data type in the legacy system.
  • Support data modeling team in defining table name and table data type as per the standards and best practices defined within the project.
  • In case of any new table in Data Warehouse, identify the source values to be uploaded in the table.
  • Provide inputs to data modeling regarding the source data for the same.
Knowledge Management:

  • Create and update knowledge articles (industry Point of View, Case studies, lessons learnt document etc) in the knowledge management repository.
  • Maintain knowledge management database.
  • Conduct training for team members on data profiling tools and techniques.
Sales Support:

  • Based on the inputs shared by the stakeholders.
  • share the inputs on RFPs on the data profiling and system analysis aspect.
  • Evaluate/ identify the tools best fit for the customer requirement.

Must Have Skills

  • Snowflake
  • Kafka
  • Azure
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