Application Architect L1(Contract)

London- 3 Days Hybrid

Role purpose
We are looking for a full stack engineer who will lead the engineering delivery and technical direction for a scalable multi-tenant data integration platform on Google Cloud Platform (GCP). The platform uses Managed Airflow (Composer) to orchestrate ETL pipelines and enables reliable movement of data from source systems through the platform into downstream vendor systems. Youll guide the team in building high-quality ETLs improving automation and deployment pipelines and implementing end-to-end data lineage with clear visual traceability of data movement.

Key responsibilities
Technical leadership & delivery
Own the technical roadmap for the platform aligning engineering outcomes to business priorities and operational resilience.
Lead solution design for new integrations and platform capabilities balancing pace with long-term maintainability.
Set engineering standards (coding testing documentation observability security) and ensure consistent adoption across the team.
Provide hands-on contribution where needed (critical ETLs framework components design spikes performance fixes).
ETL orchestration & data movement
Design and develop robust ETL pipelines orchestrated in Airflow including scheduling strategies dependency management retries backfills and processing.
Establish patterns for onboarding new source systems and delivering data to downstream vendor systems with strong reliability and traceability.
Drive data quality controls (validation reconciliation exception handling) and operational runbooks.
Platform engineering (multi-tenancy & scalability)
Evolve the multi-tenant architecture: tenant isolation configuration management metadata-driven pipelines and scalable runtime patterns.
Optimise for performance cost and reliability across environments (dev/test/prod) including capacity planning and operational SLAs.
Automation CI/CD and release engineering
Improve build and deployment automation for both platform services and Airflow DAGs (versioning packaging promotions approvals).
Implement CI/CD best practices: automated testing static analysis security scanning and controlled rollout/rollback strategies.
Reduce manual toil by investing in self-service onboarding templates and engineering enablement tooling.
Data lineage & observability
Implement end-to-end data lineage (source platform vendor) including metadata capture and a visual representation that supports auditability and faster incident resolution.
Enhance observability across pipelines and services: logging metrics alerting and dashboards; drive measurable improvements in MTTR and change failure rate.
Stakeholder management & ways of working
Partner with product owners data owners architects vendors and governance teams to shape requirements and manage delivery expectations.
Lead agile ceremonies and engineering planning; remove blockers and maintain delivery momentum.
Mentor engineers through code reviews design reviews and structured coaching; foster a culture of continuous improvement.

Required experience & skills
Proven experience as a Technical Lead / Lead Engineer delivering data engineering or integration platforms in cloud environments.
Strong hands-on experience building production-grade ETL/ELT pipelines and orchestration with Airflow.
Solid experience on Google Cloud Platform such as:
o Data services (e.g. BigQuery Cloud Storage Pub/Sub Dataflow) and/or container platforms (e.g. GKE Cloud Run)
o IAM networking secrets management and environment separation
Strong software engineering foundations: Python APIs configuration management architecture design testing strategy and performance tuning.
CI/CD expertise (pipeline tooling release controls automated quality gates) and Infrastructure-as-Code experience (e.g. Terraform).
Experience designing for reliability: retries idempotency dead-letter patterns backpressure handling and operational resilience.
Ability to translate complex technical topics for mixed audiences and drive alignment across teams.
Desirable (nice to have)
Experience implementing or integrating data lineage/metadata management tooling (e.g. Data Catalog-style metadata OpenLineage DataHub etc.).
Experience with multi-tenant platforms (tenant isolation models metadata-driven frameworks).
Knowledge of data governance concepts (data quality auditability retention access controls).
Experience integrating with external vendor systems and managing vendor technical dependencies.
Success measures (what good looks like)
Faster safer delivery of new integrations via improved automation and CI/CD.
Measurable improvement in pipeline reliability and operational outcomes (reduced incidents faster recovery).
Clear trusted end-to-end lineage view for key datasets and integrations.
Consistent engineering standards and a team thats growing capability and confidence over time.
Working style
A pragmatic hands-on technical leader who enjoys getting things done raises engineering standards without slowing delivery and builds an inclusive team environment where different viewpoints improve outcomes.