About Us

At BGBx, we're driven by a simple idea: breakthrough thinking creates breakthrough impact. As an independent commercial solutions partner to pharmaceutical and life science companies, we bring together strategists, scientists, communicators, creatives, technologists, and data experts to tackle some of healthcare's most important challenges.

Our teams work across consulting and communications to help clients shape strategy, launch innovations, engage stakeholders, and drive meaningful results throughout the product lifecycle. The work is complex, fast-moving, and deeply connected to improving lives, creating opportunities for curious minds to make a real difference every day.

If you're energized by collaboration, inspired by innovation, and motivated by work that matters, you'll find a place to grow, contribute, and make a meaningful impact at BGBx.

Position Overview

We are looking for an Infrastructure & Data Engineer with 5+ years of experience building and maintaining cloud infrastructure, data platforms, and production data pipelines. You will develop and operate reliable, scalable infrastructure that supports data processing, analytics, and other downstream applications. This is an engineering-focused role requiring strong cloud infrastructure skills, coding ability, database knowledge, and experience working with modern data and DevOps technologies.

You’ll join an AI-native engineering team that pushes modern tools hard, operates with high autonomy, and moves quickly - without compromising on security, reliability, or sound engineering principles. We actively use AI throughout the engineering lifecycle to accelerate development, investigation, documentation, and operations. At the same time, we care deeply about good architecture, maintainable systems, sensible controls, and knowing when not to automate.

Responsibilities

Design, build, and maintain cloud infrastructure and data platforms, primarily on GCP.
Develop and maintain ETL/ELT data pipelines and orchestration workflows.
Build and manage infrastructure using Terraform and infrastructure-as-code practices.
Deploy and operate containerized workloads using Docker and Kubernetes.
Develop data solutions using Python and SQL.
Work with large-scale datasets using BigQuery, GCS, and other cloud-native services.
Build and maintain CI/CD pipelines using GitHub Actions.
Implement and maintain data lineage, metadata, and data dependency tracking across pipelines and datasets.
Monitor infrastructure and pipeline health, troubleshoot failures, and optimize reliability, performance, and cost.
Manage cloud permissions, secrets, service accounts, and infrastructure security.
Support data consumers, software engineers, analysts, data scientists, and product teams.
Improve automation, observability, deployment processes, and engineering standards across the platform.
Use AI-assisted engineering tools effectively while applying appropriate review, testing, security, and operational controls.

Qualifications

5+ years of hands-on experience in infrastructure engineering, data engineering, platform engineering, or a similar role.
Strong Python and SQL skills.
Strong experience with Google Cloud Platform, particularly BigQuery and Google Cloud Storage.
Hands-on experience with Terraform or another infrastructure-as-code tool.
Experience deploying and operating workloads using Kubernetes.
Experience with an orchestration tool such as Airflow, Dagster, Prefect, or Flyte.
Experience building and maintaining CI/CD pipelines, ideally using GitHub Actions.
Strong database knowledge and experience working with cloud-based data infrastructure.
Understanding of data lineage, metadata management, data quality, and dependencies between data pipelines.
Familiarity with cloud IAM, networking, secrets management, monitoring, and logging.
Strong troubleshooting and problem-solving skills.
Comfortable working in an AI-native development environment and using AI tools as part of day-to-day engineering.
Strong engineering judgement, including the ability to balance speed with security, maintainability, and reliability.