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Analytics Engineer

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Job specification

We are seeking an analytics engineer to help us build out self service analytics capabilities to serve the wider organisation. The person will need to work with the various business users, data analysts, data engineers, data architects, application engineering and the product team to understand the key organisational entities and use this knowledge to build out data marts and our metrics store. The analytics engineer will also work closely with the data analytics chapter lead who will help drive data literacy and training programs across the organisation to drive the adoption of self-serve analytics. In addition to this the user will from time to time help business users with analytics directly when the users don’t have the ability to self-serve and when they don’t have a dedicated data analyst; this will help build empathy with the users and inform gaps in the data marts and metrics store that need to be addressed. The candidate will also work with the experimentation platform team to surface the metrics in our experimentation tooling.

 

There will need to be strong appreciation for data quality and data governance with value being assigned to consistently producing high quality metadata to support discoverability and consistency of calculation and interpretation. 

 

A solid understanding of the retail banking domain is desirable, but not required. 

 

Candidates should have experience across the following systems and languages:

  • Experience with at least one self-serve data analytics tool such as Looker, Tableau, PowerBI, etc.
  • Ideally GCP, but strong experience in another platform such as AWS or Azure will suffice
  • Cloud data warehouses such as BigQuery, Redshift or Snowflake
  • Workflow scheduler such as Apache Airflow
  • Experience programming in Python
  • Proficient in SQL
  • Comfortable writing detailed design documents

 

Additional desired experience includes:

  • Familiarity with dbt
  • A good understanding of relational databases as well as some exposure to NoSQL databases such as MongoDB
  • Familiarity with the ELT paradigm and tools such as Fivetran, Stitchdata or Airbyte 
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Lokasi
Tanggal posting
16 September, 2022