SQL Data Engineer

Prediktive - Latin America, LATAM

We are looking for a SQL Data Engineer based anywhere in Latin America to work on a long term project for one of our clients, a Data Analytics and Business Intelligence services company based in Los Angeles.



This role will maintain and extend our Client's Microsoft SQL Server based ETL pipeline and datamarts to support ongoing business needs. This role will work closely with the VP of Engineering and the Managing Director for the Sales division to ensure data quality and smooth operations for a system responsible for ingesting 30+ nightly exports from the end customers into our Client's datamart that powers the Sales product. This role will also be responsible for onboarding new end customers into the system. As our Client migrates away from SQL Server to Cloud Native (12-18 months) this role will adopt management of new cloud native pipelines built on open source components such as Apache Airflow, Python and Apache Beam / Cloiud Dataflow on the Google Cloud Platform.

While a standard Microsoft SQL Server database administrator would normally suffice for this role we have a special requirement that the candidates for this role are capable of building and maintaining software written in C# on the .NET framework. This is due to our Client's use of C# within SQL Server SSIS to perform transformations on data. For this role the ideal candidate should have a software engineering background ideally on the Microsoft stack - C#, .NET, SQL Server. Desire and willingness to learn Python a plus if the candidate is excited about building cloud native data platforms.



  • Advanced level of English
  • Extensive experience with Microsoft SQL Server and it’s SSIS (integration services) components used for ETL
  • Experience with T-SQL – Microsoft’s SQL language – for building data analytics, datamarts, data warehouses, ETL
  • Ability to read, write and understand C# and .NET to maintain C# functions that are part of our ETL pipeline in Microsoft SQL Server SSIS packages
  • Advanced understanding of common database design principles like normalization, snowflake, etc.

Posted On: Wednesday, October 24, 2018

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