• Contribute to maturing our cloud security posture management practice across our cloud environments • Ship CI/CD security integrations that developers actually use • Partner with infrastructure enablement and product teams to embed security into the workflows they already use • Help shape our AI security programme at scale • Participate in the on-call rotation and build runbook quality and post-incident reviews

• Develop and maintain reports, dashboards, and analytics using OTBI and BI Publisher • Collaborate with HR business partners and stakeholders to gather reporting requirements and translate them into technical specifications • Create and modify BI Publisher data models and build RTF or Excel‑based report templates • Build and customize OTBI analyses and dashboards to deliver real‑time HR insights • Write and optimize SQL queries to support complex data extraction and reporting needs • Provide ongoing support for existing reports, including troubleshooting data issues and implementing enhancements • Assist in testing and validating new reports and system upgrades to ensure data integrity • Support reporting needs across Core HR, Benefits, Compensation, and related HCM modules

• Design, develop, and implement scalable and reliable data solutions on the Microsoft Azure platform. • Collaborate with cross-functional teams to gather and analyze data requirements. • Design and implement data ingestion pipelines to collect data from various sources, ensuring data integrity and reliability. • Perform data integration and transformation activities, ensuring data quality and consistency. • Implement data storage and retrieval mechanisms, utilizing Azure services such as Azure SQL Database, Azure Data Lake, and Azure Blob Storage. • Monitor data pipelines and troubleshoot issues to ensure smooth data flow and availability. • Implement data quality measures and data governance practices to ensure data accuracy, consistency, and privacy. • Collaborate with data scientists and analysts to support their data needs and enable data-driven insights.

Role Description We run a distributed, camera-based video monitoring and AI alerting platform. The estate spans an AWS-hosted fleet of services and workers, a GPU-backed computer-vision inference pipeline, a real-time streaming and presence layer, and thousands of on-premise edge "media boxes" that ingest camera feeds, serve video, and stream events back to the cloud. Today the bulk of our backend is ~140 Java 8 services and libraries that have grown over many years. We are building their successor: a clean, modern Python monorepo (trella), and we are migrating capabilities over to it service by service. We are looking for a Senior Python Engineer: a strong programmer first, with real depth in both Python and Java to lead and execute that migration. You will design and build the new Python services, port existing Java functionality across with its behaviour intact, and occasionally maintain and fix the existing Java stack while it remains in production. This is a builder's role at the centre of a major platform modernization. What you'll work on: - The new Python platform (primary) - A greenfield, strongly-opinionated monorepo built for the long term: - Python 3.14, managed with uv workspaces (libs/, packages/, svcs/, apps/, scripts/), scaffolded from Copier templates. - FastAPI services with Strawberry GraphQL as the primary data API; REST where it's the right fit; Uvicorn ASGI. - psycopg3 straight against PostgreSQL / TimescaleDB using the repository pattern - deliberately no ORM - with yoyo migrations. - Pydantic / pydantic-settings for models, validation, and config; httpx for outbound HTTP; pendulum for datetimes; structlog + OpenTelemetry for observability. - Strict engineering standards, enforced in CI: full type annotations under a strict mypy config, ruff lint + format, and a curated, opinionated set of approved libraries (alternatives are banned at the linter level, on purpose). - A strong testing culture: pytest, TestClient, async tests, real test databases. - The legacy Java stack (occasional, ongoing) - ~140 Java 8 services and libraries: REST APIs, SQS/SNS workers, Lambda functions built with Gradle and Bazel, running on Jetty 9.4, deployed to Elastic Beanstalk, ECS, and Lambda. - Domains include alerts, analytics, API, auth, clips, media, presence, notifications, and partner integrations. - You'll read this code to understand behaviour before porting it, keep it healthy with bug fixes and small changes while it's still live, and decommission pieces as their Python replacements land. - The platform around it - AWS (us-west-2): EC2/ECS, Lambda, S3, RDS (PostgreSQL/TimescaleDB), ElastiCache (Redis), MSK (Kafka), Kinesis & Kinesis Video Streams, IoT Core, Cognito, SQS/SNS/SES. - A GPU-backed computer-vision inference tier producing the alerts that reach parents' phones. - Edge appliances (Linux + Docker) in the field, reachable over AWS IoT. What you'll do: - Design and build new Python services in the monorepo (schema, data access, business logic, APIs, and tests) to a high, consistent standard. - Migrate functionality from Java to Python: study an existing Java service, capture its real behaviour and edge cases, and re-implement it idiomatically in Python without regressions. - Maintain the Java stack as needed: diagnose and fix production issues, make targeted changes, and keep services healthy until they're retired. - Set and uphold engineering standards in the new codebase: typing, structure, the libs/svcs separation, the repository pattern, testing, and review quality. - Work with data: model schemas in PostgreSQL/TimescaleDB, write correct and efficient SQL, and design migrations. - Own your work end to end: from design through deploy, observability, and on-call follow-through, and drive it to a durable resolution. Qualifications - Strong software engineer first. Excellent fundamentals: data structures, concurrency, API and data modelling, testing, and writing code others can maintain. - Senior-level Python in production: idiomatic, fully typed, well-tested. Comfort with async, packaging, and a modern toolchain (type checkers, linters, virtual envs). - Solid Java in production: able to confidently read, debug, and modify a large existing Java codebase, and reason about its behaviour well enough to port it. - Strong with relational databases (PostgreSQL preferred) writing SQL directly rather than leaning on an ORM, and designing schemas and migrations. - Hands-on AWS experience building and operating real services. - Migration / modernization mindset: you can hold "match the old behaviour" and "build it right for the next ten years" in your head at the same time. - A bias for follow-through: you find what's actually needed, focus on it, and finish. - Excellent English communication. Nice to have: - FastAPI, GraphQL (Strawberry or similar), and async Python at scale. - uv, monorepo workflows, and strict typing (mypy) / ruff in CI. - TimescaleDB or other time-series data. - Gradle and/or Bazel builds; Jetty; AWS Lambda. - Messaging and streaming: Kafka/MSK, SQS/SNS, Kinesis. - Containers (Docker/ECR/ECS), CircleCI, and infrastructure-as-code (Terraform). - Auth with Cognito, JWT/OIDC, or Entra; partner-integration work. - Computer-vision / ML-adjacent systems, IoT, or edge/on-premise fleets.