Bandsintown powers live-music discovery for over 100 M fans and 700,000 artists . Our data platform drives real-time event intelligence, artist analytics, and large-scale marketing automation across the global live-music ecosystem. We're expanding our distributed data engineering team to build the next generation of high-throughput ingestion , streaming , and real-time serving systems .

If you love Spark , Airflow , AWS , and building resilient data platforms , you'll feel right at home. THE ROLE You'll design, build, and operate the distributed systems that move and transform mission-critical data across Bandsintown. You'll work spec-first , own your components end-to-end, and build pipelines that are idempotent, restartable, observable, and built for scale .

This is a hands-on role for engineers who thrive in high-volume, real-time environments and want to see their work directly impact millions of users.

WHAT YOU WILL DO Build streaming & Distributed systems Create high-throughput pipelines using Spark, Kinesis, EMR, Glue, and AWS serverless. Build restartable, observable Airflow DAGs for both batch and streaming workloads. Implement real-time ingestion with proper partitioning, offset management, watermarking, and backpressure.

Engineer for scale & reliability Architect systems for high availability, horizontal scalability, and real-time serving. Define SLIs/SLOs, instrument everything with Cloud Watch, structured logs, and Grafana dashboards.

Build dashboards that answer: "Is the data product actually working?" Own AWS data platform components Build pipelines using Airflow, Kinesis, EMR/EMR Serverless, Glue, Lambda, ECS, Athena. Implement serverless ingestion,



event-driven architectures, and distributed compute. Enforce IAM least privilege, Secrets Manager, and dependency hygiene (Snyk, Dependabot). Work spec-first with AI assistance Write clear technical specs before coding.

Use Claude

Code, Cursor, Copilot to accelerate development while keeping architecture tight.

Maintain

Backstage entries and service docs as living artifacts. Collaborate & take ownership Partner with product, architecture, Dev Ops, BI, and Data Science. WHAT YOU BRING Required 5+ years building large-scale distributed systems and data pipelines.

Deep experience with: Spark ; Airflow (idempotent, restartable DAGs) ; AWS ingestion stack (Kinesis, EMR, Glue, Lambda, ECS, Cloud Watch). Strong programming skills in Python, Py Spark . Solid SQL and experience with Postgre SQL, My SQL, Redshift , or similar. Solid distributed systems fundamentals (partitioning, consistency, backpressure).

Experience with observability : Cloud Watch, Grafana, structured logs, alerting.

Experience with CI/CD (Buildkite, Git Hub Actions, Jenkins). Comfortable using AI coding tools in a spec-first workflow. Nice-to-Have Experience supporting ML/AI pipelines.

Experience with Snowflake, Iceberg, dbt, Druid, Trino.

Experience with Data Hub or similar catalogs. A passion for live music. WHY BANDSINTOWN Build systems used by 100 M+ fans and 700,000 artists. Join a high-leverage, AI-native engineering culture. Work in a small, senior team where your components matter. 4 weeks vacation, plus flexible summer hours. Full health coverage from day one. A human-centered culture with real ownership, creativity, and room to grow.

📌 Développeur/euse back-end big data (Montreal)
🏢 Bandsintown Group
📍 Montreal