The API Services team is responsible for engineering and delivering cutting-edge services to aide in content delivery to end customers. These services support 110 news brands, and more than 110 million unique monthly visitors.

The Principal Data Engineer will play a key role in architecting, developing and maintaining the data architecture for Gannett’s new Content Platform that supports the content production & delivery systems that are consumed by both our network of 3000 journalists & our customer facing products. You will be expected to design & consume large scale, fault tolerant and highly available architectures. A large part of your role will be forward looking, with an emphasis on optimizing content structures & relationships. If you have a passion for rapid development, automation, learning, challenging and bettering your peers, with a strong desire to operate in a full stack environment, you’d probably fit in well here.

Responsibilities:

• Collaborate with stakeholders & developers to identify data needs & ideal implementation.

• Contribute to the architecture and vision of Gannett’s content data pipeline.

• Track record of evolving complex data environments.

• Continuously evaluate data usage patterns and identify areas of improvement.

• Interface closely with data scientists and engineering to ensure reliability and scalability of data environment.

• Drive future state technologies, designs and ideas across the organization.

• Provide planning for two-week sprints.

• Provide day to day operational support for our applications.

• Improve and establish best practice around our application and infrastructure monitoring.

Automate everything:

• Containerizing applications with Docker

• Scripting new solutions/APIs/services to reduce toil

• Research new tools to optimize cost, deployment speed and resource usage

• Assist in improving our onboarding structure and documentation.

Responsibility Breakdown:

• 30% – Data architecture design / review

• 20% – Mentoring

• 15% – Application Support

• 15% – Planning / Documentation

• 10% – Design applications / recommendations / poc

• 10% – New Technology Evaluation

Technologies:

Systems:

• Linux

• Couchbase

• Elastic Search

• Solr

• Neo4j

• Other NoSQL Databases

Exciting things you get to do:

• Engineering high-performant applications with an emphasis on concurrency

• Agile

• Amazon Web Services, Google Compute Engine

• Google DataStore, Spanner, DynamoDB

• Docker, Kubernetes

• Database testing

• GraphQL

• Fastly

• Terraform

• Monitoring with NewRelic

Minimum Qualifications:

• Deep experience in ETL design, schema design and dimensional data modeling.

• Ability to match business requirements to technical ETL design and data infrastructure needs.

• Experience using search technologies like Elasticsearch and Solr and designing the integration of search with a persistent data store.

• Deep understanding of data normalization methodologies.

• Deep understanding of both Relational and NoSQL databases.

• Experience with data solutions like Hadoop, Teradata, Oracle.

• Proven expertise with query languages such as SQL, T-SQL, NRQL, solr querying.

• Self-Starter that can operate in a remote-friendly environment.

• Experience with Agile (Scrum) and test driven development, continuous integration and version control (GIT).

• Experience deploying to Cloud compute or container hosting.

• Experience working with data modeling tools.

• Basic understanding of REST APIs, SDKs and CLI toolsets.

• Understanding of web technologies.

• Experience with Data in a media industry is a plus.