Role Description
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.
You'll 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.
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
- Data services (eg, BigQuery, Cloud Storage, Pub/Sub, Dataflow) and/or container platforms (eg, GKE, Cloud Run)
- IAM, networking, secrets management, and environment separation
Strong software engineering foundations
- Python
- APIs
- configuration management
- architecture design
- testing strategy
- performance tuning
CI/CD expertise
- pipeline tooling
- release controls
- automated quality gates
- Infrastructure-as-Code experience (eg, Terraform)
Experience designing for reliability
- retries
- idempotency
- dead-letter patterns
- backpressure handling
- operational resilience
Ability to translate complex technical topics for mixed audiences: Drive alignment across teams.
Desirable (nice to have)
Experience implementing or integrating data lineage/metadata management tooling (eg, 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 that's 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.