Senior Cloud Engineer

Responsibilities

• Architect and lead the implementation of complex data automation solutions that replace manual workflows with scalable, reliable data pipelines across the organization.
• Design and build end‑to‑end Bronze → Silver → Gold transformation pipelines, implementing domain logic, data quality frameworks, and reproducible data products.
• Own the design of the data platform architecture, including ingestion frameworks, transformation patterns, orchestration strategies, and data governance standards.
• Establish and enforce data engineering best practices, including schema evolution, data contracts, validation frameworks, and performance optimization across all data pipelines.
• Build scalable backend data services and APIs that expose curated datasets to analytics tools, product applications, and downstream consumers.
• Lead the integration of data sources from operational systems, external applications, and sensor data, implementing both batch and streaming patterns as needed.
• Partner closely with product teams, data analysts, business stakeholders, and AI Engineers to understand complex data requirements and translate them into robust technical solutions.
• Drive technical excellence by establishing architectural standards, conducting design reviews, and documenting patterns that enable team scalability and maintainability.
• Evaluate and recommend data technologies, tools, and platforms that will improve engineering productivity and data platform capabilities.

Qualifications

• A degree in Computer Science, Mathematics, or a related field.
• 5+ years of experience as a Cloud Engineer, Data Engineer, Backend Engineer, or similar role with demonstrated technical leadership.
• Proven experience architecting and maintaining complex data pipelines, transformation workflows, and data platform components that serve multiple downstream consumers.
• Proven experience building event‑driven and streaming data integrations at scale.
• Expert knowledge of cloud data services across either Azure or AWS ecosystems (e.g., ADLS, ADF, Databricks, Event Hubs, S3, Glue, EMR, Kinesis, Lambda).
• Production experience deploying and managing containerized services in Kubernetes environments (AKS and/or EKS preferred).
• Strong expertise with SQL and NoSQL systems (e.g., Postgres, MongoDB, Redis) including schema design and optimization.
• Knowledge of data governance processes and tools and metadata management solutions.
• Experience with infrastructure as code and platform engineering practices (e.g., Terraform).
• Experience implementing and maintaining CI/CD workflows (Azure Pipelines, GitHub Actions, AWS CodePipeline/CodeBuild, ArgoCD).
• Strong understanding of access control frameworks and security governance in hybrid environments, including integration with enterprise identity providers (e.g., Active Directory/LDAP, SSO, IAM federation).
• Good programming skills in Python.
• Excellent communication and leadership skills, with proven ability to influence technical direction.

Preferred Qualifications

• Strong experience designing and operating data platforms supporting telemetry, sensor, location, and operational technology (OT) data workloads.
• Experience processing and managing large‑scale video, image, and unstructured media datasets, including streaming ingestion and analytics workflows.
• Understanding of feature engineering patterns and data preparation workflows supporting machine learning systems.
• Strong understanding of private cloud and on‑premises environments, including secure service design, network isolation, and hybrid connectivity patterns between on‑prem and public cloud.
• Experience working with maritime, fleet, vessel operations, logistics, or industrial operational domains, including telematics, tracking, asset monitoring, or operational analytics use cases.

Salary

Up to £95,000 per annum.