Data engineer (senior) – agileengine
join the agileengine team as a senior data engineer (id43916). Agileengine is an inc. 5000 company that creates award‑winning software for fortune 500 brands and trailblazing startups across 17+ industries.
Why join uswe’re a people‑first culture, recognized with multiple best place to work awards. We value growth, impact, and care.
About the roleas a data engineer, you’ll play a key role in ensuring smooth and successful device launches through observability, test automation, and real‑time launch support. Transform raw telemetry into actionable insights, build dashboards and anomaly detection systems, and automate data validation workflows. This role offers opportunity to work on cutting‑edge devices, collaborate cross‑functionally, and directly impact product reliability and customer experience.
What you will do
turn raw device telemetry into actionable alerts with strong observability, data quality, and launch support baked in.
Work with cross‑functional teams to establish device observability and health monitoring.
Define logging, metrics, and traces for device and pipeline health, and ship dashboards for latency, uptime, error rates, and crash signals.
Add anomaly detection over telemetry and logs and track health kpis during launches.
Develop automated anomaly detection for logging anomalies in device telemetry.
Build dashboards to track device health and ensure all data artifacts have proper quality, integrity, and reliability.
Participate in remote or on‑site go‑lives to monitor device health and triage issues in real time using dashboards.
Collaborate with qa to ensure access to proper data and pipelines for testing and build automations as needed.
Develop tooling to simulate various on‑device scenarios for launch‑readiness.
Support on‑site testing and live device launches remotely by monitoring device health based on metrics and dashboards.
Triage issues in real time by analyzing logs and identifying failure sources to enable rapid resolution and successful launches.
Must haves
5–8+ years of experience in data engineering with spark (structured streaming) or similar tools in production.
Proficiency in python and strong sql/pandas skills.
Solid understanding of streaming fundamentals.
Experience building alerting, monitoring, or observability systems.
Experience turning manual checks into automated guardrails.
Comfortable supporting live device rollouts and post‑launch monitoring.
Upper‑intermediate english level.
Perks and benefits
professional growth: mentorship, techtalks, and personalized growth roadmaps.
Competitive compensation: usd‑based compensation and budgets for education, fitness, and team activities.
A selection of exciting projects: modern solutions development with fortune 500 clients and top‑tier product brands.
Flextime: tailor your schedule for an optimal work‑life balance, with options to work from home or the office.
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