Senior Cloud Data Engineer (Remote)

CameraMatics · Remote · posted Sep 21, 2026

Open to candidates worldwide

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seniorSaaS

What this role actually asks for

Extracted by RemoteHunt

Must have

  • 5+ years in data engineering or backend engineering
  • Strong Python
  • Production experience with AWS Lambda
  • Deep SQL and relational database skills
  • Hands-on with Kinesis, Airflow, Flink, EMR/Spark, DynamoDB, OpenSearch
  • Experience debugging data quality issues in production
  • Comfortable owning ambiguous problems end-to-end

Nice to have

  • Grafana/CloudWatch observability tooling
  • Data retention, GDPR/compliance-driven data lifecycle work
  • Exposure to LLM/GenAI tooling
  • Telematics, IoT, or high-volume time-series data domains
  • AWS cost optimization experience

Tools and technologies

AWSPythonKinesisFlinkEMRAirflowSQLPostgreSQLMySQLLambdaDynamoDBOpenSearchGrafanaCloudWatchAthena

The full posting

Who we are We’re on a mission to transform how fleets operate, using cutting-edge camera technology, AI, machine learning and telematics to make roads safer and businesses smarter. As an award-winning SaaS company in a high-growth phase, we’re scaling fast and expanding into new markets worldwide. Our technology gives fleet operators real-time visibility, reduces risk, improves efficiency, and helps set new safety standards across the industry. Join a global, ambitious team and be part of what's next! The role 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, and Airflow-orchestrated ETL for customer reports
  • Data reliability & quality: deduplication, schema validation, data completeness checks, and 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, and audit trails
  • Performance & cost engineering: RDS reader/writer routing, query optimization, OpenSearch shard/index tuning, and 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 What we’re looking for Essential:
  • 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 Nice to have:
  • 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) Why join CameraMatics? 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.

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