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About the Role

We are seeking a Technical Delivery Lead to drive the engineering and technical strategy for a scalable, multi-tenant data integration platform built on Apache Airflow and Google Cloud. In this role, you will lead the delivery of production-grade data pipelines and cloud solutions, working closely with cross-functional teams to align technical efforts and ensure reliable, high-quality outcomes using modern DevOps and infrastructure-as-code practices. This position is ideal for a hands-on technical leader with strong Python and GCP experience who thinks in terms of reliability and resilience, and who can translate complex technical concepts clearly for diverse audiences while guiding teams in a collaborative environment.

Responsibilities

Lead the engineering and technical strategy for a scalable multi-tenant data integration platform leveraging Apache Airflow and GCP technologies.
Build and maintain production-grade ETL/ELT pipelines orchestrated with Apache Airflow.
Utilize container platforms such as GKE and Cloud Run.
Apply strong software engineering skills in Python, APIs, configuration management, testing, and performance tuning.
Implement CI/CD pipelines, release controls, automated quality gates, and Infrastructure-as-Code (Terraform).
Design for reliability including retries, idempotency, dead-letter patterns, and operational resilience.
Translate complex technical concepts to diverse audiences and align cross-team efforts.
Work with GCP BigQuery for large-scale data warehousing and analytics.
Architect cloud solutions using GCP Cloud Architecture best practices.

Requirements

7+ years of experience in data engineering or data platform engineering, with at least 3 years in a technical lead or delivery lead capacity.
Proven experience owning a technical roadmap and aligning engineering delivery with business priorities.
Strong hands-on experience designing and building production-grade ETL/ELT pipelines orchestrated with Apache Airflow (or Cloud Composer).
Strong experience with GCP services including BigQuery, GKE, and Cloud Run, applying GCP cloud architecture best practices.
Proficiency in Python, with strong software engineering skills across APIs, configuration management, testing, and performance tuning.
Working experience with Terraform and CI/CD pipelines, including release controls and automated quality gates.
Experience designing resilient systems using patterns such as retries, idempotency, and dead-letter handling.
Experience implementing data quality controls, including validation, reconciliation, and exception handling.
Experience establishing engineering standards for coding, testing, documentation, observability, and security.
Excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences and align cross-team efforts.
Strong analytical, debugging, and problem-solving skills.

Skills

Python
GCP
Apache Airflow
Google Cloud
DevOps
Infrastructure-as-Code
ETL/ELT
GKE
Cloud Run
APIs
Configuration Management
Testing
Performance Tuning
CI/CD
Terraform
Reliability
Resilience
BigQuery
Cloud Architecture
Data Lineage
Metadata Management
Multi-tenant Architectures
Data Governance
Vendor System Integrations
Data Engineering
Data Platform Engineering
Technical Roadmap Ownership
Business Priorities Alignment
Cloud Composer
Release Controls
Automated Quality Gates
Retries
Idempotency
Dead-letter Handling
Data Quality Controls
Validation
Reconciliation
Exception Handling
Engineering Standards
Coding Standards
Testing Standards
Documentation Standards
Observability
Security
Written Communication
Verbal Communication
Analytical Skills
Debugging
Problem-Solving
GCP Professional Data Engineer Certification
GCP Professional Cloud Architect Certification
Tenant Isolation
Metadata-driven Pipelines
Dataplex
Data Catalog
OpenLineage
DBT
Great Expectations
Third-party Source System Integration
Event-driven Services
Streaming Services
Pub/Sub
Dataflow
Observability Tooling
Cloud Monitoring
Cloud Logging
Datadog
Banking
Insurance
Regulated Financial Services

Location

Great Britain

Work Type

Full-time

Experience Level

7+ years of experience in data engineering or data platform engineering
at least 3 years in a technical lead or delivery lead capacity

About the Company

Bits In Glass (BIG) operates as a rapidly expanding AI and automation consultancy, maintaining presence throughout Canada, the United States, India, and Great Britain.
The firm's technical scope encompasses over ten primary platforms across artificial intelligence, cloud infrastructure, data management, automation solutions, and enterprise software.
Honoured internationally as a Great Place to Work and recipient of various partner achievement awards, BIG emphasizes team collaboration, technological innovation, and tangible client outcomes.
Our staff consists of skilled engineering professionals dedicated to tackling difficult technical problems, driving joint success, and guiding enterprise organizations through digital transformation with certainty.