Senior Software Engineer - Data

The Role

As a Senior Data Engineer at Bitly, you will join a high-performing data engineering team building the next-generation data platform that powers analytics, experimentation, and ML / AI driven product features used by millions of people. You will design, build, and operate production-grade data systems that deliver trusted data to internal teams and customer-facing applications, across both streaming and batch workloads.

Bitly operates globally across every major platform, processing billions of events each month. Our data infrastructure includes hundreds of servers, dozens of services, and multiple real-time streams. You will help scale the platform’s reliability, performance, and cost efficiency, and build the foundational primitives (event modeling, streaming pipelines, and governed data access) that enable teams to move faster with confidence.

What You’ll Do

• Own and scale core data platform systems that power analytics, experimentation, and ML / AI driven product features at scale; designed for high throughput, reliability, and cost efficiency
• Design, build, and operate production-grade data services and pipelines end-to-end, with clear SLAs/SLOs, monitoring, and operational runbooks
• Build real-time and near-real-time streaming pipelines for high-volume event ingestion and processing across product and analytics use cases
• Ensure event correctness at scale, including event-time vs processing-time semantics, watermarking/late data handling, replay/backfills, idempotency/deduplication, and schema evolution strategies
• Deliver core behavioral analytics capabilities such as sessionization, identity stitching, bot filtering, and attribution to support product insights and customer-facing analytics
• Design flexible internal and external data interfaces (APIs, datasets, contracts) that enable self-serve consumption while maintaining strong governance
• Establish and enforce engineering and data quality standards: testing strategy, code review norms, documentation, data contracts, lineage, anomaly detection, and automated validation/observability
• Optimize performance and cost across distributed processing and storage (partitioning, clustering, query tuning, resource sizing, and workload management), and lead initiatives that reduce latency and improve reliability
• Partner cross-functionally (product, DS/ML, engineering, analytics, marketing, finance) to define event instrumentation and data requirements and to deliver critical platform capabilities on time
• Mentor and raise the bar: guide peers on system design and implementation approaches, champion software engineering best practices in data engineering, and drive a culture of technical rigor and continuous improvement

Who You Are

• 6+ years building and operating production data systems on cloud platforms (strong hands-on GCP experience), with ownership of reliability, performance, and cost
• Strong software engineering fundamentals: system design, maintainable code, testing, CI/CD, and debugging distributed systems
• Hands-on experience with streaming and event-driven architectures, including event-time semantics, late data, replay/backfills, deduplication, and schema evolution
• Experience building sessionization and behavioral analytics pipelines, including identity resolution and high-cardinality event modeling
• Expert in SQL and Python, with strong data modeling and reusable framework experience
• Familiar with modern data stacks: orchestration (Airflow / Cloud Composer), transformation (dbt), distributed processing (Dataflow), and lakehouse/warehouse patterns
• Clear communicator and mentor who can translate ambiguous problems into scalable technical solutions
• Experience with Infrastructure-as-Code (Terraform) and operating data platforms via CI/CD and containerized environments (Docker/Kubernetes)
• Good to have: Backend service development experience (using Go)