- Design, develop and maintain analytical models to provide insight on platform telemetry for performance and utilisation analytics, development of the DevOps framework to monitor, tune, and improve the models to address performance objectives and inquiries
- Collaboration with platform teams to utilize existing data products, ingestion patterns, or automation, avoid bespoke development while contributing to the enhancement and creation of these shared assets when gaps are identified
- Own the technical data lifecycle and corresponding technology stack for their data domain and to have a deep understanding of the bp technology stack.
- Write, deploy and maintain software to build, integrate, manage, maintain, and quality-assure data, and responsible for deploying secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline.
- Adhere to and advocate for software engineering best practices (e.g. technical design and design review, testing, monitoring & alerting, code review, documentation).
- Deep and hands-on experience (typically 10+ years) in designing, planning, prototyping, productionizing, deploying, maintaining and documenting reliable and scalable data science solutions in complex environments that have yielded business impact
- Deep and hands-on experience in deriving actionable insights from data and quantifying business impact, preferably with experience on developing insights and analytics on enterprise platform operations
- Familiarity with data infrastructure and data management technologies
- Recent experience utilizing data analytics offerings and services from Azure and AWS
- Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++); advanced SQL knowledge.
- Experience designing and implementing large-scale distributed systems
- Statistics and Machine Learning: understand and have applied a wide range of statistical or machine learning methods to build data science algorithms (e.g. for forecasts, ranking) or carry out advanced data analytics (e.g. product A/B testing, causal inference from observational data)
- Data Manipulation: understand the lifecycle of the data and the data systems deployed in your team; make changes to the data tech stack; write and maintain advanced data pipelines; expert SQL skills; handle all types of data (e.g. streaming, structured, unstructured data)
- Coding: contribute to internal and/or external libraries through raising issues, adding documentation and/or contributing new features; write clean, re-usable code in a language that runs in production at bp.
- Right approach / tool choice: deep understanding of a wide range of commonly available Data Science approaches and tools and choose the right ones to solve the problem
- Scalability, Reliability, Maintenance: proven experience in building scalable and re-usable systems and automating operations
- Data Domain Knowledge: proven understanding of data sources and data and analytics requirements and typical SLAs associated to data provisioning and consumption at enterprise scale, with experience in analysis of data or other enterprise platform operations activities.
#LI-HO1Critical to achieving bp's digital ambitions is the delivery of our high value data and analytics initiatives, and the enablement of the technologies and platforms that will support those objectives.
As a Data Engineer you will be developing and maintaining data infrastructure and writing, deploying and maintaining software to build, integrate, manage, maintain, and quality-assure data at bp. You are passionate about planning and building compelling data products and services, in collaboration with business stakeholders, Data Managers, Data Scientists, Software Engineers and Architects in bp.
You will be part of bp's Data & Analytics Platform organisation, the group responsible for the platforms and services that operate bp's big data supply chain. The portfolio covers technologies that support the life cycle of critical data products in bp, bringing together data producers and consumers through enablement and industrial scale operations of data ingestion, processing, storage and publishing, including data visualisation, advanced analytics, data science and data discovery platforms.
For this role specifically, you will be in our data platform performance management team focused on metrics and insights. This will involve designing and delivering the necessary data workflows and pipelines to collect and process data in order to provide visibility and insights to our platform operations and performance, including cost of operations, runtime and systems utilization analysis, opportunities for improvement, etc. The ultimate objective is to create a data-driven organisation within the Data & Analytics Platform team, and be able to build a 'mission control' station that will allow us to detect, anticipate and prevent issues, have insights to improve our operations, and have timely access to data that will allow our data platform engineers to build the necessary automation for a self-healing, etc. Further we want to exploit our data to understand non-technical measures and insights related to adoption and engagement, various measures of utilization, value contribution and delivery, quality assurance related to governance and compliance or identification of technical debt, and other scenarios that our leadership teams or platform engineers may challenge us on.