IoT Data Engineer / Data Scientist (Telemetry)

# Job Title: IoT Data Engineer / Data Scientist (Telemetry) 1 Position
## About the Job
We are looking for a pragmatic, data-driven IoT Data Engineer / Data Scientist to own telemetry data pipelines, analytics and ML-driven insights for our deployed fleet of devices. You will work across ingestion, storage, time-series modelling, anomaly detection and operational reporting turning raw sensor streams into reliable, actionable products for engineering and customers. This is a hands-on role that requires both strong software/data engineering skills and practical data science experience with streaming and time-series telemetry.
## Responsibilities
- Design, build and operate telemetry ingestion pipelines (MQTT/HTTP ? broker ? stream processing ? storage).
- Build robust ETL/ELT processes for time-series sensor data: validation, normalization, enrichment and backfill.
- Implement data models and schemas for efficient storage and querying of telemetry (TSDBs, columnar stores, object stores).
- Develop feature engineering, anomaly detection and predictive maintenance models for device health, battery, and performance metrics.
- Collaborate with firmware, connectivity and cloud teams to design telemetry formats, sampling strategies and on-device summarization.
- Deploy, monitor and maintain ML models and analytics in production (A/B testing, model retraining pipelines, drift detection).
- Create dashboards, reports and alerts (business & engineering) to surface telemetry insights and KPIs.
- Instrument data quality metrics, SLAs and observability for the data stack.
- Produce reproducible notebooks, documented experiments and handover notes for cross-team consumption.
- Mentor junior data engineers/scientists and help improve data literacy across the company.
## Qualifications
**Required**
- Degree in Computer Science, Data Science, Electrical Engineering, Statistics, or equivalent experience.
- 3+ years experience building data pipelines, analytics or ML systems; at least some work with IoT/telemetry or time-series data.
- Strong Python skills (pandas, numpy); solid SQL skills for complex time-series queries.
- Experience with streaming technologies (Kafka, Kinesis, MQTT workflows) or message brokers.
- Familiarity with time-series databases / TSDBs (InfluxDB, TimescaleDB) or efficient columnar/object-store architectures.
- Practical ML experience: anomaly detection, forecasting, classification for time-series; familiarity with scikit-learn and one deep-learning framework is a plus.
- Experience deploying models: Docker, CI/CD, model monitoring; familiarity with MLflow, TFX or similar is a plus.
- Comfortable with cloud platforms (AWS/GCP/Azure) and managed services for storage, compute and orchestration.
- Strong debugging, data validation and documentation skills; clear communicator in English.
**Nice-to-have**
- Domain experience with energy systems, UPS, battery telemetry or industrial sensors.
- Experience with edge analytics / on-device inference or TinyML.
- Familiarity with protobuf/avro schemas, data contracts and telemetry compression techniques.
- Experience with visualization tools (Grafana, Superset, Power BI).
## What We Offer
- A cross-disciplinary product team where your work directly impacts device reliability and customer value.
- Opportunity to shape the telemetry & ML roadmap from first principles.
- Competitive compensation, training budget and flexibility for remote/hybrid work.
- Access to real-world fleet data and opportunities to publish/communicate findings.
## How to Apply
Please send the following to **[HIDDEN TEXT]** with subject line **IoT Data Engineer / Data Scientist (Telemetry) Application**:
1. CV (12 pages).
2. Short cover note (max 200 words) explaining relevant telemetry/data experience and earliest availability.
3. One sample deliverable (notebook, GitHub repo, technical write-up or dashboard link) demonstrating time-series or ML work.
4. Two references (name, role, contact) or one recent employer contact.
Shortlisted candidates will be invited for a technical screening and a practical discussion about telemetry design and a short take-home or shared notebook exercise. We welcome applicants from diverse backgrounds and encourage practical, production-minded candidates to apply.