At a Glance
- Tasks: Build and operate data services for the Royal Navy's maritime operations.
- Company: Join a leading engineering team focused on innovative data solutions.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with potential for career advancement in a collaborative environment.
- Why this job: Make a real impact by enhancing maritime domain awareness through data engineering.
- Qualifications: Experience in data services, strong Python and SQL skills, and problem-solving abilities.
The predicted salary is between 72000 - 88000 £ per year.
We are seeking a Data Integration & Geo Services Engineer to join a Capability Engineering team delivering data platforms and pipelines that underpin operational and analytical services supporting Royal Navy Maritime Domain Awareness outputs. This is a hands-on engineering role, focused on building and operating containerised data and integration services within enterprise on-premise environments that collect, process, enrich and disseminate data across enterprise and geospatial platforms. You will work across the technology stack and will be expected to understand and troubleshoot the infrastructure, operating systems, networking, storage and platform services upon which data services depend. You will work across the full data lifecycle, from ingestion through to delivery, ensuring data is accessible, trusted and usable. You will take new and existing sources of operational data and engineer reliable ways to acquire, process, store, enrich, and disseminate them. This may involve APIs, streaming data, enterprise messaging, spatial data, databases and geospatial platforms. The emphasis is on solving integration and data engineering problems rather than working with any single product or technology. Experience with enterprise GIS technologies such as ESRI ArcGIS Enterprise would be advantageous but is not essential. We are primarily seeking experienced data engineers with strong engineering fundamentals who can apply those skills across a range of enterprise data technologies.
What You Will Do
- Working within established engineering processes and standards, you will:
- Design, build and maintain data acquisition services to ingest information from APIs, message brokers, file systems, sockets, sensors and other enterprise data sources.
- Develop and support event-driven and streaming data services using enterprise messaging and integration platforms.
- Design and implement integrations between enterprise platforms, message brokers, APIs, databases, geospatial applications and external data providers.
- Design and implement mechanisms for secure dissemination of data through APIs, message brokers, file-based exchange and other operational interfaces.
- Contribute to the solution design activities, selecting appropriate storage, processing and dissemination approaches for new data sources and requirements.
- Ensure data quality, integrity and availability across platforms.
- Monitor and optimise data pipelines for performance and reliability.
- Troubleshoot and resolve complex data and platform issues.
- Contribute to automation and CI/CD of data services.
- Collaborate with stakeholders to understand and deliver data requirements.
- Produce technical documentation, runbooks and operational artefacts.
What We Are Looking For
Essential
- Experience engineering and supporting data services within on-premise or self-managed hosting environments, with an understanding of the underlying infrastructure and platform dependencies.
- Experience building and maintaining data pipelines.
- Experience diagnosing and resolving issues in operational production services.
- Strong Python and SQL skills.
- Experience working with structured data and databases.
- Understanding of event-driven architectures and messaging platforms.
- Understanding of data modelling and transformation techniques.
- Experience with Linux environments.
- Strong problem-solving and analytical skills.
- Ability to work independently within defined standards.
- Ability to learn and apply unfamiliar technologies to solve engineering problems.
Desirable
- Experience with container orchestration tools or enterprise data platform technologies.
- Experience with streaming and messaging platforms such as Apache Kafka.
- Experience with CI/CD pipelines, infrastructure automation and DevOps working practices.
- Experience developing or supporting containerised applications within Kubernetes environments.
- Experience with enterprise GIS platforms and geospatial data technologies (e.g. ESRI ArcGIS Enterprise, GeoEvent, Velocity, spatial databases).
- Experience integrating enterprise platforms using REST APIs and automation.
- Experience working with object storage platforms and S3-compatible interfaces.
- Experience in secure or regulated environments.
- Experience implementing data exchange solutions across security domains or controlled information environments.
- Familiarity with service management tools (e.g. Jira, Confluence).
ESRI Data Engineer in Portsmouth employer: Carbon 60
At Carbon 60, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. Located in Harlow, this hybrid role offers flexibility and the chance to engage with a dedicated Quality team, ensuring your contributions directly impact our commitment to quality excellence. With opportunities for professional growth and development, joining us means being part of a forward-thinking company that values your expertise and dedication.
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We think this is how you could land ESRI Data Engineer in Portsmouth
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We think you need these skills to ace ESRI Data Engineer in Portsmouth
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
