We are looking for a Software Engineer to join Hearst Magazines Digital Media. The role will have a data focus, working closely not only with platform developers and software architects, but also with data product managers, data analysts and data scientists on various data initiatives, including building performance reporting and AI/ML-based features into the platform. The ideal candidate is an experienced software engineer who is also experienced in building data pipelines, wrangling data, and has a strong interest in building data products from the ground up.
Hearst Magazines Digital Media reaches more than 100 million people around the world every month on digital platforms connected to loved and trusted global brands like Cosmopolitan, Delish, Esquire, Elle, Car & Driver, and Runner's World (to name a few). The platform operates on a microservice architecture: at its core is a set of relational databases accessed by both Restful and GraphQL API endpoints, in turn powering 40+ applications written in a range of languages including Python, Go, React, and PHP.
We are building new platform features that leverage advanced data modeling, ML, and AI (both home-grown and off-the-shelf), and this hire will play a key role in the development and QA of custom data models, pipelines, and APIs to support these features.
Hearst Magazines Digital Media's business side uses Google's entire suite of enterprise software, from DFP to Google Analytics to Google AdWords to Google Optimize, as well as a number of content distribution channels including Facebook, Snap, Pinterest, Outbrain, and Taboola. We expect this role to help maximize and scale our usage of these platforms by deepening our integrations via their APIs.
For custom analytics, we use a combination of BigQuery and Looker. We are looking for somebody to own the entire Looker stack, including the administrative, infrastructural, software (LookML) layer, reporting, and API integrations, so that we can scale analytics across the business at large.
The role is based out of our Emmaus, PA office. We work in SCRUM, but being self-directed and comfortable multitasking is a must.
Responsibilities for Software Engineer
Be part of a development team that innovates and creates modern tools and features that will be used across the entire Hearst content platform.
Participate in key software design, working directly with other engineers, the product team, devops, and the editorial team.
Architect, write code, complete programming and perform testing and debugging of data applications.
Build data APIs and data delivery services that support critical operational and analytical applications for our internal business operations, customers and partners.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build and optimize extraction, transformation, and loading of data from a wide variety of data sources using SQL, AWS, GCP and other 'big data' technologies.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Qualifications for Software Engineer
The ability to take a feature or service to full completion, from working with our back-end tech through front-end implementation
Expert SQL knowledge and experience working with relational databases, query authoring, as well as familiarity with a variety of databases.
Experience building and optimizing 'big data' data pipelines, architectures and data sets.
Knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
Strong analytic skills related to working with unstructured datasets.
Experience supporting and working with cross-functional teams in a dynamic environment.
3+ years of experience in a Software Engineer role, with B.S./M.S. in Computer Science or a related field, or equivalent experience.
Experience or familiarity with the following software/tools:
Big data tools: Hadoop, Spark, Kafka, etc.
Relational SQL and NoSQL databases, e.g. Postgres and Cassandra.
Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
AWS cloud services: EC2, EMR, RDS, Redshift
GCP cloud services: BigQuery, Cloud Storage, etc.
BI tools: Looker, Domo, Tableau, etc.
Stream-processing systems: Storm, Spark-Streaming, etc.
Object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
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