Senior Data Engineer, Ring Data Science and Engineering ID-9064

Description

Come build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what’s important?

About Ring

We started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone? What if you could be there without needing to actually, you know, be there? After many late nights and endless tinkering, our first Video Doorbell was born.

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That invention has grown into over a decade of groundbreaking products and next-level features. And at the core of all that, everything we’ve done and everything we’ve yet to build, is that same inventor's spirit and drive to bridge the distance between people and what they care about. Whatever it is, at Ring we’re committed to helping you be there for it.

(https://www.ring.com)

About The Role

The Senior Data Engineer within Ring Data Science and Engineering plays a pivotal role in shaping how we architect analytics and data science solutions to operate data-driven decision making at scale across all business units, carry the voice of our customers, inform business and product strategy with data, and provide a quality data foundation for AI.

Key job responsibilities

Role

We are seeking an experienced Senior Data Engineer to lead the technical designs of data lakes, data warehouses, and data pipelines within the Ring Data Science and Engineering org. In this role, you will:

  • Own the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs
  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using AWS services and internal tools
  • Design efficient and scalable data warehouse models.
  • Be responsible for design and code reviews.
  • Build and deliver high quality data sets to support data scientists and customer reporting needs.
  • Identify opportunities to leverage AI for increased productivity.
  • Drive improvements in automation and quality.
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
  • Find and create ways to measure the customer experience to drive business outcomes.
  • Recognize and adopt best practices in data engineering: integrity, design, analysis, validation, and documentation.
  • Troubleshoot operational quality issues.
  • Review and audit existing jobs and queries.
  • Recommend improvements to back-end sources for increased accuracy and simplicity.

A day in the life

You'll collaborate with multiple teams of data, business intelligence, software, and systems development engineers shaping our data strategy through vision setting, data governance, and operational excellence; fostering an inclusive culture that encourages empathy, experimentation, and innovation. You will guide your teams in balancing strategic thinking with company objectives, and collaborate with key cross-functional leaders and teams to work backwards from the customer to ideate, validate, and execute business opportunities at the forefront of the data engineering landscape. This will include overseeing the regular application of techniques involving extracting, transforming, and loading very large datasets, architecting data platforms for feature performance, maintainability, and scale, measuring and improving data quality, and driving measurable business impact.

Basic Qualifications

  • Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
  • 5+ years of data engineering experience
  • Experience mentoring team members on best practices
  • Expert-level skills in writing and optimizing SQL
  • 2+ years development experience in python or similar scripting language for automation
  • 3-4+ years of work experience with ETL, Data Modeling, and Data Architecture with terabytes of data
  • 1+ years experience working with distributed computing and associated technologies such as Spark, EMR, etc.
  • 2+ years experience with Redshift. Tangible experience working with Redshift Spectrum, AWS Glue, and S3

Preferred Qualifications

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience operating large data warehouses
  • 5+ years of work experience with ETL, Data Modeling, and Data Architecture.
  • Experience or familiarity with newer AWS data and analytics tools such as AWS Lake Formation, Sagemaker, DynamoDB, Lambda, Kinesis, ElasticSearch
  • 2-3+ years experience working with core AWS data and analytics services. Understand of the applicability, limitations, and tradeoffs between a wide set of AWS database and analytics technologies.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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