Data Platform Engineer II

Key Skills

Aartificial intelligence, Apache Hive, Apache Kafka, AWS, Azure, C# Programming, C++, Data Engineering, Data Lake, Data science techniques, DataOps, DevOps, Elasticsearch, Google Cloud Platform (GCP), Java Programming, Kubernetes-K8s, Lakehouse, Machine learning techniques, MLOps tools, Presto, Python Programming, Scala Programming, SPARK Programming

Job Description

At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. ​

We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:​

• Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics.”​

• Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent.​

• Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time.

• Automation of end-to-end data flows: Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in <12h)

• Enabling governance by design of external and internal data:  with engineered practical solutions for controlled use and monitoring

• Innovative disease-specific and domain-expert specific data products: to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles.

• Supporting e2e code traceability and data provenance: Increasing assurance of data integrity through automation, integration

• Improving engineering efficiency: Extensible, reusable, scalable, updateable, maintainable, virtualized traceable data and code​ would be driven by data engineering innovation and better resource utilization.

We are looking for a skilled and experienced Data Platform Engineer II to join our growing team. Data Platform Engineers take full ownership of delivering high-performing, high-impact data platform as products, and services, from a description of a problem customer Data Engineers are trying to solve all the way through to final delivery (and ongoing monitoring and operations). 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 ensuring their services are meeting customer demand, having an impact, and iterate to deliver and improve on those metrics in an agile fashion.

The Data Platform team builds and manages reusable components and architectures designed to make it both fast and easy to build robust, scalable, production-grade data products and services in the challenging biomedical data space.

A Data Platform Engineer II is a technical individual contributor, building modern, cloud-native systems for standardizing and templatizing data engineering, such as: 

• Standardized physical storage and search / indexing systems 

• Schema management (data + metadata + versioning + provenance + governance) 

• API semantics and ontology management 

• Standard API architectures 

• Kafka + standard streaming semantics 

• Standard components for publishing data to file-based, relational, and other sorts of data stores 

• Metadata systems 

• Tooling for QA / evaluation etc. 

A Data Platform Engineer II knows the metrics desired for their tools and services and iterates to deliver and improve on those metrics in an agile fashion.

Additional responsibilities include: 

• Given a well-specified data framework problem, implement end-to-end solutions using appropriate programming languages (e.g., python, Scala, or go), open-source tools (e.g., Spark, Elasticsearch, ...), and cloud vendor-provided tools (e.g., Amazon S3) 

• Leverage tools provided by Tech (e.g., infrastructure as code, cloud Ops, DevOps, logging / alerting) in delivery of solutions. 

• Write proper documentation in code as well as in wikis/other documentation systems. 

• Write fantastic code along with proper unit, functional, and integration tests for code and services to ensure quality. 

• Stay up to date with developments in the open-source community around data engineering, data science, and similar tooling​.​

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• Bachelor's degree with 5+ years' experience or Master's degree with 3+ years' experience in computer science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering

• Experience with common distributed data tools in a production setting (Spark, Kafka, Hive, Presto, etc.)

• Experience with specialized data architecture (e.g., data lake, lake house, data fabric, data mesh, optimizing physical layout for access patterns)

• Experience with public cloud providers like AWS, Azure and GCP

• Experience with search / indexing systems (e.g., Elasticsearch)

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

• Experience building and designing a DevOps first way of working.

• Demonstrated excellence writing production Python, Java, Scala, Go, and/or C#/C++

• Practical experience with agile software development and DevOsps-forward ways of working

• Demonstrated experience building reusable components on top of the CNCF ecosystem including platforms like Kubernetes (or similar ecosystem)

• Metrics-first mindset

LI-GSK

GSKOnyx

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:

• Agile and distributed decision-making – using evidence and applying judgement to balance pace, rigour and risk.

• Managing individual and team performance.

• Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.

• Implementing change initiatives and leading change.

• Sustaining energy and well-being, building resilience in teams.

• Continuously looking for opportunities to learn, build skills and share learning both internally and externally.

• Developing people and building a talent pipeline.

• Translating strategy into action - a compelling narrative, motivating others, setting objectives and delegation.

• Building strong relationships and collaboration, managing trusted stakeholder relationships internally and externally.

Budgeting and forecasting, commercial and financial acumen.

The annual base salary for new hires in this position ranges from $115,974 to $156,906 taking into account a number of factors including work location, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.

Please visit GSK US Benefits Summaryto learn more about the comprehensive benefits program GSK offers US employees.