Salarios :Negociable / Competitivo
Ciudad de México, Ciudad de México

Descripción

This role is a key leadership position inside our Advanced Analytics Center of Excellence (CoE), where you will have the responsibility of owning and evolving our data infrastructure, empowering Business Area Leads with insights from data analytics and visualization. This is primarily a hands-on technical role requiring business acumen and leadership abilities, as you will manage a team of data engineers, scientists, and BI analysts from a technical standpoint.

This role has a strong career growth potential. Advanced Analytics is a key strategic priority and we aim to leverage a cutting-edge infrastructure to develop and productionize proprietary machine learning models. This is chance to be leading the development of a high-powered business unit and transform retail in Mexico.

You will partner with and report to our Chief Strategy & Analytics Officer, an ex-Senior Engagement Manager at McKinsey and QuantumBlack, McKinsey´s Advanced Analytics firm.


Responsibilities:

  • You will lead a team of data/backend engineers, data scientist and business intelligence analyst from a technical standpoint.
  • You should have past management experience of such profiles and feel comfortable having a conversation with each of them while leading their specialized efforts towards achieving business goals.
  • You will partner with Business Area Leads, form, articulate and defend independent viewpoints while having the ability to seamlessly translate technical and business needs in both directions.


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Requisitos

Technical requirements:

- Coding and modelling:
  • Strong coding and algorithmic skills are essential. You will be coding, participating and leading implementation. You are expected to be able to perform code reviews and correct code for other engineers following best practices.
  • You should especially master Python and SQL at a high level. A big part of our infrastructure is written in Python, and we use relational models for all our products (it is a good sign if you have a strong opinion on whether that is a good idea or not).
  • Strong data modeling skills are necessary. You should be able to build a data model for a project, starting from MVP all the way up to production while optimizing for performance and cost. Indexing, partitioning, and normalization techniques should come naturally to you.
  • Backend coding will be required to interface systems, so you should be able to implement and design an API from scratch. Knowledge of Go (golang) is a strong plus, but any other backend language is enough.

- Infrastructure:
  • You should be familiar with non-relational and graph databases.
  • Knowledge of best practices for Data Warehousing, and/or ability to quickly research and understand existing implementations and adapt to use cases.
  • Knowledge of Spark, Hive, Glue, Athena, Redshift and/or other big data frameworks and tools and their function within a data infrastructure is required.
  • Familiarity with AMQP, Kafka and general publish-consume patterns.
  • Essential DevOps skills. You are expected to be able to deploy the minimal infrastructure to run your code, as well as design and guide implementation of more complex deployment pipelines.
  • Experience with AWS a plus.
  • Familiarity with serverless frameworks a plus.
  • Knowledge of container and container orchestration frameworks.

- Visualization and Business:
  • Ability to understand and model KPIs from diverse domains. You will interact with all departments within the company and are expected to be able to handle a conversation with managers on their terms, while translating their needs to technical implementations in a proactive manner.
  • Familiarity with CRM systems, Salesforce especially, a plus.
  • Experience with Apex (Java) a plus.
  • Experience with data visualization, by means of Tableau-like products and front-end libraries for dashboard design and implementation.
  • Proactive ability to translate technical needs and requirements to and from non-technical stakeholders. Someone will come to you with a great idea and you will be expected to design and implement it as a production ready system, design and collect metrics, report on its performance, iterate and maintain it.
  • Ability to do all of the above with no guidance. You are the expert. It is fun.

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