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Senior Cloud Data Engineer (Remote)

Role overview

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)
  • Hands-on with Kinesis (or Kafka), Airflow, Flink, EMR/Spark, DynamoDB, OpenSearch/Elasticsearch

Responsibilities

  • Streaming batch pipelines: Kinesis-based event ingestion, Flink processing, EMR batch reprocessing/replay
  • Data reliability quality: deduplication, schema validation, data completeness checks
  • Data observability: building out Grafana dashboards with recency/frequency KPIs
  • Performance cost engineering: RDS reader/writer routing, query optimization, AWS cost optimization

Key facts

Hard skills

Other skills

  • Problem Solving
  • Collaboration
  • Communication

About the company

CameraMatics logo

CameraMatics

Internet of Things (IoT) Platforms

CameraMatics is a driver-centric cloud platform that empowers fleet operators and drivers to continuously improve performance and safety with enhanced visibility and digitized smart processes. Our platform can be deployed to any vehicle type and translates big data from onboard vehicular sensors, smart cameras, and driver apps to support driver safety, load security and continuous learning and improvement.

Company details

Company typeScaleup
IndustryInternet of Things (IoT) Platforms
Company size51 - 200

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Job description

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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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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