Note: The job is a remote job and is open to candidates in USA. ActivTrak is growing its data engineering team to build and operate scalable, observable, reliable, and economical production systems for machine learning and analytics. The Senior Data Engineer will own data pipeline infrastructure, orchestration, deployment mechanisms, observability, scalability, and operational reliability across a petabyte-scale platform.
Responsibilities
- Designing and operating production data pipelines across a layered (bronze/silver/gold) data platform: sourcing, cleansing, and transforming data at scale
- Solving incremental sync and stream processing as data volume and account count grow — a real, unsolved scaling problem for us today
- Building regional data architecture that respects data residency and PII boundaries (e.g., data belonging to a region can't simply be centralized into one global store)
- Designing the production systems, orchestration, and deployment mechanisms that turn Data Science's models and analysis into durable, monitored, reliable pipelines
Skills
- 5+ years designing and operating data pipelines in production at scale
- Experience with batch and stream data processing, including incremental/streaming architectures
- Strong Python and production-grade software engineering practices (testing, code review, version control, monitoring)
- Demonstrably strong SQL
- Experience with ETL/ELT pipeline design and orchestration
- Experience with regional/multi-region data storage and data residency constraints
- Parallel dataframes (Dask, Spark, or similar)
- API design/implementation (microservices, REST, etc.)
- Cloud environment experience (GCP or AWS), Docker/Containers, Kubernetes
- Machine learning deployment or serving experience
Benefits
- Position is remote within US
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