Senior Cloud Data Engineer (AWS)

Location: Portugal or Ireland; fully remote

Company

hirify.global is a SaaS company developing camera technology, AI, machine learning, and telematics products that help fleet operators improve road safety, efficiency, and compliance.

What you will do

• Build and operate Kinesis-based event ingestion, Flink processing, EMR batch replay, and Airflow-orchestrated ETL pipelines.
• Develop data reliability controls, including deduplication, schema validation, completeness checks, and root-cause analysis of production data-quality issues.
• Build Grafana observability dashboards with recency and frequency KPIs across alerts, trips, ingestion, and reporting.
• Implement manifest-driven data retention and audit trails across RDS, DynamoDB, S3, and OpenSearch.
• Optimize database performance and cloud costs through query tuning, routing, partitioning, index and shard tuning, and AWS resource optimization.
• Own workstreams from architecture and design documentation through implementation, deployment, and production monitoring.

Requirements

• 5+ years of experience in data engineering or backend engineering with a strong data focus.
• Strong Python and production experience with AWS Lambda and serverless patterns.
• Deep SQL and relational database knowledge, including PostgreSQL or MySQL, query optimization, partitioning, and locking behavior.
• Hands-on experience with several of Kinesis or Kafka, Airflow, Flink, EMR or Spark, DynamoDB, and OpenSearch or Elasticsearch.
• Experience debugging production data-quality issues and building validation and monitoring systems.
• Ability to own ambiguous problems end-to-end, write design documents, scope tickets, and drive deployment.

Nice to have

• Grafana, CloudWatch, or Athena federated query experience.
• Experience with data retention and GDPR or compliance-driven data lifecycle work.
• Exposure to LLM or GenAI tooling, including RAG, knowledge bases, or evaluation frameworks such as LangFuse.
• Experience with telematics, IoT, or high-volume time-series data.
• AWS cost optimization experience, including reserved capacity and instance right-sizing.

Culture & Benefits

• Fully remote, remote-first collaboration with structured communication.
• Sprint-based delivery with daily standups, ticket triage, and design sessions.
• Small senior engineering team where work ships directly to production and affects customers.
• AI-assisted development is actively encouraged.
• Opportunity to work with AWS, streaming and batch processing, observability, and high-volume data systems.