
51 - 200 employees
Founded 2013
☁️ SaaS
⚡ Productivity
🏢 Enterprise
SaaS • Productivity • Enterprise
ActivTrak is a leading platform in workforce analytics, offering robust solutions for employee productivity monitoring, workforce management, and productivity measurement. With over 9,500 organizations utilizing its services, ActivTrak helps improve productivity and performance through insightful productivity reports, AI-driven coaching, and customizable dashboards. Its comprehensive features support time tracking, schedule adherence, capacity planning, engagement detection, and technology optimization. ActivTrak is dedicated to transforming workforce efficiency and security, facilitating data-driven decisions for enhanced performance and productivity management.
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51 - 200 employees
Founded 2013
☁️ SaaS
⚡ Productivity
🏢 Enterprise
SaaS • Productivity • Enterprise
ActivTrak is a leading platform in workforce analytics, offering robust solutions for employee productivity monitoring, workforce management, and productivity measurement. With over 9,500 organizations utilizing its services, ActivTrak helps improve productivity and performance through insightful productivity reports, AI-driven coaching, and customizable dashboards. Its comprehensive features support time tracking, schedule adherence, capacity planning, engagement detection, and technology optimization. ActivTrak is dedicated to transforming workforce efficiency and security, facilitating data-driven decisions for enhanced performance and productivity management.
• Design and operate production data pipelines across a layered bronze/silver/gold data platform • Source, cleanse, and transform data at scale • Solve incremental synchronization and stream processing challenges as data volume and account count grow • Build regional data architecture that respects data residency and PII boundaries • Design production systems, orchestration, and deployment mechanisms for Data Science models and analysis • Build durable, monitored, reliable pipelines for production machine learning and analytics • Own pipeline infrastructure, orchestration, deployment mechanisms, observability, scalability, and operational reliability • Collaborate with Data Science when production issues span model and platform • Operate as an individual contributor without people-management responsibilities
• 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, including testing, code review, version control, and monitoring • Demonstrably strong SQL • Experience with ETL/ELT pipeline design and orchestration • Experience with regional/multi-region data storage and data residency constraints • Experience with parallel dataframes such as Dask, Spark, or similar • API design and implementation experience, including microservices and REST • Cloud environment experience with GCP or AWS • Experience with Docker/containers and Kubernetes • Machine learning deployment or serving experience
• Remote within the US • Minimal travel • Limited physical demands • Opportunity to own the platform problem determining ML and analytics scalability • Meaningful scaling challenges involving incremental/streaming processing, regional data residency, and petabyte-scale data • Small, senior team with real ownership and visibility to leadership • Equal opportunity and inclusive work environment
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