[Hiring] Senior Cloud Data Engineer @CameraMatics

Role Description

You'll join the CameraMatics data team building and operating the data platform behind our fleet telematics products — ingestion pipelines, alerting and reporting systems, and customer-facing data features at production scale on AWS. You'll own critical workstreams end-to-end: from architecture and design docs through implementation, deployment, and production monitoring.

What you'll do

• Streaming & batch pipelines:
  • Kinesis-based event ingestion
  • Flink processing
  • EMR batch reprocessing/replay
  • Airflow-orchestrated ETL for customer reports
• Data reliability & quality:
  • Deduplication
  • Schema validation
  • Data completeness checks
  • Root-cause investigation of data quality issues in customer-facing reports
• Data observability:
  • Building out Grafana “mission control” dashboards with recency/frequency KPIs across alerts, trips, ingestion, and reporting
• Data lifecycle & compliance:
  • Manifest-driven data retention enforcement across heterogeneous stores (RDS, DynamoDB, S3, OpenSearch)
  • Per-org retention policies
  • Audit trails
• Performance & cost engineering:
  • RDS reader/writer routing
  • Query optimization
  • OpenSearch shard/index tuning
  • AWS cost optimization across Lambda, DynamoDB, and S3

How the Team works

• Sprint-based delivery with daily standups, ticket triage, and design sessions
• Remote-first with structured collaboration; AI-assisted development actively encouraged
• Small senior team where your work ships to production and directly affects customers

Qualifications

• 5+ years in data engineering or backend engineering with heavy data focus
• Strong Python; production experience with AWS Lambda and serverless patterns
• Deep SQL and relational database skills (PostgreSQL/MySQL) — query optimization, partitioning, locking behavior
• Hands-on with at least several of: Kinesis (or Kafka), Airflow, Flink, EMR/Spark, DynamoDB, OpenSearch/Elasticsearch
• Experience debugging data quality issues in production and building validation/monitoring to prevent recurrence
• Comfortable owning ambiguous problems end-to-end: writing design docs, scoping tickets, and driving to deployment

Requirements

• Grafana/CloudWatch observability tooling; Athena federated queries
• Data retention, GDPR/compliance-driven data lifecycle work
• Exposure to LLM/GenAI tooling (RAG, knowledge bases, eval frameworks like LangFuse)
• Telematics, IoT, or high-volume time-series data domains
• AWS cost optimization experience (reserved capacity, instance right-sizing)

Benefits

• A genuinely impactful role, building the data platform behind products that help fleet operators improve safety, efficiency and compliance.
• A collaborative, ambitious team, working alongside a small, senior engineering team where ideas are encouraged, collaboration is valued and AI-assisted development is embraced.
• The opportunity to make a visible impact quickly. By owning meaningful data engineering challenges end-to-end, with the autonomy to shape solutions and see your work go directly into production.
• The chance to work with modern technology at scale. Getting hands-on with AWS, Python, streaming and batch data processing, observability and high-volume data systems.
• Grow with a scaling global business as our products, customers and markets continue to expand.