Job Description

: We are looking for a savvy Data Engineer to join our growing Local Products team. The hire will be responsible for expanding and optimizing our data modeling and data pipeline architecture. The ideal candidate is an experienced engineer who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, data analysts, data scientists and will ensure optimal data delivery architecture is consistent throughout ongoing projects. The candidate must be self-directed and comfortable in supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing current data architectures to support our next generation of local products and data initiatives. Responsibilities Create and maintain optimal data pipeline architecture, Assemble complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and GCP cloud resources technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Keep our data separated and secure across national boundaries through multiple data centers and regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Requirements: Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Strong analytical skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable data stores. Strong organizational skills. Experience supporting and working with cross-functional teams in a dynamic environment. Solid experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with relational SQL and NoSQL databases, including Postgres, MySQL, MongoDB (including sharding patterns and replica sets techniques) Experience with database scalabilty and availability Experience with GCP resources Experience with object-oriented/object function scripting languages (such as Python, Golang, Shell scripting) is a plus.

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