Analytics Engineer

Job Summary

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Good storytelling starts with great listening. At Audible, that means each role and every project has our audience in mind. Because the same people who design, develop, and deploy our products also happen to use them. To us, that speaks volumes.

About This Role

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The Audible Global Insights and Data Science group seeks an Analytics Engineer to support the success of our mission critical data initiatives. In this role, you will be part of an international team of analysts and data scientists, developing data assets that power our wide ranging suite of data products, from BI frameworks to data science models.

You will contribute to a data-driven culture by helping teams transform their business requirements into foundational data systems that provide standardization and consistency across metrics and dimensions. You will work across the entire business and be exposed to a wide range of functions from engineering and data science, to marketing, product management and content development.

You will be able to work with minimal oversight, conduct multiple tasks simultaneously, develop and deploy data pipelines, contribute to the code repository, perform code reviews and quality assurance checks, and help guide others in best practices on analytics engineering practices. Critical to the success of this role is your ability to work with big data while developing expertise on a wide range of tools and systems within a vast data infrastructure ecosystem. And just as critical as the technical requirements are soft skills such as effective collaboration within a cross-functional team, and clear and compelling communication of requirements and recommendations.

About You

You are able to work with relatively minimal instruction and oversight, conduct multiple tasks and projects simultaneously, collaborate with cross functional stakeholders, and own deliverables end-to-end. You have the ability to work with big data, have a meticulous eye for detail and consistency, and enjoy architecting clean data sets by modeling data and metrics to empower employees to make data-driven decisions with accurate information.

You enjoy enabling and scaling self-serve analytics for team members across the organization. You take pride in seeing your work represented across all spectrums of data products, knowing you have developed the foundation on which others are reliant upon. And you embody the Audible people principle of “Imagine and Invent Before They Ask’ by bringing creative ideas around data, processes and pipelines that will advance the team to the next stage.

As an Analytics Engineer, you will...
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Collaborate with data professionals and business stakeholders to translate business objectives and product requirements into tangible data assets.
Develop, deploy, maintain and monitor data pipelines in support of business intelligence and data science data products.
Continuously evolve and optimize data assets within the data warehouse through enhancement and deprecation initiatives.
Contribute and optimize the code repository that contains all business logic, and conduct ongoing code reviews and quality assurance as part of a CI/CD process.
Enhance the data catalog through documentation of business logic and data transformations.
Facilitate data governance by enforcing standardization and consistency of core business metrics and dimensions.
Help to define and improve our internal standards for code best practices, including style, readability, and maintainability.
Codify and democratize best practices, and coach/advise other team members on data modeling, SQL query optimization & reusability.

Basic Qualifications

3+ years experience working in a data or analytics engineering role.
Superior SQL skills, with experience transforming raw data into clean models, optimizing SQL performance, and troubleshooting & improving others' code.
Strong understanding of data warehousing concepts (e.g. ELT, schema management, materialization) and data modeling concepts (e.g. Star Schema).
Experience in designing, building, and administering modern data pipelines within data warehouses.
Experience with Snowflake, BigQuery, or Redshift.
Experience with version control tools such as Github or Gitlab.
Experience with business intelligence solutions (Looker, Tableau, Periscope, Mode).
Experience collaborating with multiple business functions and stakeholders to develop metrics and key insights.
Proficiency with Python.

Preferred Qualifications

Clear and direct communication skills about complex, technical topics.
Excellent communication and project management skills with a customer service focused mindset.

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