Technical Delivery Lead

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.

Bits in Glass UK 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.

Roles and 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. (Desirable: Experience with data lineage/metadata management tools, multi-tenant architectures, data governance, and vendor system integrations).

Required Skills

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.

Nice to Have

GCP Professional Data Engineer or Professional Cloud Architect certification.

Experience designing or enhancing multi-tenant data platforms, including tenant isolation and metadata-driven pipelines.

Experience with data lineage and metadata management tools such as Dataplex, Data Catalog, or OpenLineage.

Experience with data governance and data quality frameworks such as DBT or Great Expectations.

Experience integrating and onboarding vendor or third-party source systems.

Experience with event-driven or streaming services such as Pub/Sub or Dataflow.

Experience with observability tooling such as Cloud Monitoring, Cloud Logging, or Datadog.

Experience in banking, insurance, or other regulated financial services environments.

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. Our staff consists of skilled engineering professionals dedicated to tackling difficult technical problems, driving joint success, and guiding enterprise organisations through digital transformation with certainty.