Bandsintown powers live-music discovery for over 100M 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 ROLEYou'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 DOBuild streaming & Distributed systemsCreate 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 & reliabilityArchitect systems for high availability, horizontal scalability, and real-time serving.Define SLIs/SLOs, instrument everything with CloudWatch, structured logs, and Grafana dashboards.Build dashboards that answer: "Is the data product actually working?"Own AWS data platform componentsBuild 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 assistanceWrite transparent 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 ownershipPartner with product, architecture, DevOps, BI, and Data Science.WHAT YOU BRINGRequired5+ 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, CloudWatch).Strong programming skills in Python, PySpark.Strong SQL and experience with PostgreSQL, MySQL, Redshift, or similar.Solid distributed systems fundamentals (partitioning, consistency, backpressure).Experience with observability: CloudWatch, Grafana, structured logs, alerting.Experience with CI/CD (Buildkite, GitHub Actions, Jenkins).Comfortable using AI coding tools in a spec-first workflow.Nice-to-HaveExperience supporting ML/AI pipelines.Experience with Snowflake, Iceberg, dbt, Druid, Trino.Experience with DataHub or similar catalogs.A passion for live music.WHY BANDSINTOWNBuild systems used by 100M+ 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. #J-18808-Ljbffr

📌 Développeur/Euse Back-End Big Data (Montreal)
🏢 Bandsintown Group
📍 Montreal