Sr. Data Ops Engineer
Site Name: UK - Hertfordshire - Stevenage, UK - London - Brentford, USA - Pennsylvania - Philadelphia, USA - Pennsylvania - Upper Providence Posted Date: Aug 17 2021 The mission of the Data Science and Data Engineering (DSDE) organization within GSK Pharmaceuticals R&D is to get the right data, to the right people, at the right time. The Data Framework and Ops organization ensures we can do this efficiently, reliably, transparently, and at scale through the creation of a leading-edge, cloud-native data services framework. We focus heavily on developer experience, on strong, semantic abstractions for the data ecosystem, on professional operations and aggressive automation, and on transparency of operations and cost. We are looking for an experienced Sr. Data Ops Engineer to join our growing Data Ops team. The Data Ops team accelerates biomedical and scientific data product development and ensures consistent, professional-grade operations for the Data Science and Data Engineering organization by building templated projects (code repository plus DevOps pipelines) for various Data Science / Data Engineering architecture patterns in the challenging biomedical data space. Sr. Data Ops Engineers take full ownership of delivering high-performing, high-impact biomedical and scientific data ops products and services, from a description of a pattern that customer Data Engineers are trying to use all the way through to final delivery (and ongoing monitoring and operations) of a templated project and all associated automation. They are standard-bearers for software engineering and quality coding practices within the team and are expected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project. They devise useful metrics for ensuring their services are meeting customer demand and having an impact and iterate to deliver and improve on those metrics in an agile fashion. A Sr. Data Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizing biomedical and scientific data engineering, such as: Cloud Infrastructure-as-Code Service and Flow orchestration Data as a configurable resource (including configuration-driven access to scientific data modeling tools) Operability (monitoring, alerting, logging, tracing, ...) Code coverage and quality checks GitOps-based software development lifecycle Audit as a service Additional responsibilities also include: Partner with Tech where modifications to underlying tools (e.g. infrastructure as code, Cloud Ops, DevOps, logging / alerting, ...) are needed to serve new use cases and to ensure operations are planned Write fantastic code along with the proper unit, functional, and integration tests for code and services to ensure quality. Mentor more junior engineers in these skills Stay up to date with developments in the open-source community around DevOps, data engineering, data science, and similar tooling. Spot opportunities to test out new tooling for internal use cases, as well as opportunities to contribute back to the community. The DSDE team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. Why you? Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: Master's in computer science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering, etc, 5+ years experience (or PhD plus 3 years job experience) Demonstrated experience with software engineering (testing, documentation, software development lifecycle, source control, …) Demonstrated experience with DevOps tools and concepts (e.g. Jira, GitLabs / Jenkins / CircleCI / Azure DevOps / …) Demonstrated experience with common distributed data tools in a production setting (Spark, Kafka, etc) Experience with specialized data architecture (e.g. optimizing physical layout for access patterns, including bloom filters, optimizing against self-describing formats such as ORC or Parquet, etc) Experience with search/indexing systems (e.g. Elasticsearch) Experience with Agile development in Python, Scala, Go, and/or C++ Demonstrated experience building reusable components on top of the CNCF ecosystem including Kubernetes Experience with schema tools/schema management (Avro, Protobuf) Preferred Qualifications: If you have the following characteristics, it would be a plus: Experience with specialized data architecture (e.g. optimizing physical layout for access patterns) Experience with search/indexing systems (e.g. Elasticsearch) Experience building and designing a DevOps first way of working Experience mentoring junior engineers into deep technical expertise Metrics-first mindset Why GSK? Our values and expectations are at the heart of everything we do and form an important part of our culture. These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities: Operating at pace and agile decision making - using evidence and applying judgement to balance pace, rigour and risk. Committed to delivering high-quality results, overcoming challenges, focusing on what matters, execution. Continuously looking for opportunities to learn, build skills and share learning. Sustaining energy and wellbeing Building strong relationships and collaboration, honest and open conversations. 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