Open to remote roles · Tunis, UTC+1 · EU work authorization
Data engineer who owns pipelines end to end: ingestion, ClickHouse and BigQuery storage, data-quality monitoring and cost per event. I migrated critical analytics from MySQL to ClickHouse and designed the roadmap for ~20x more events.
The Quantic Factory · Paris, remote
The Quantic Factory · Paris, remote
Client and company code is private, so these are described by problem and outcome.
Problem: Analytics queries on 10M+ records were too slow for real-time diagnostics.
What I did: Designed a two-node ClickHouse cluster and migrated from MySQL with a blue-green strategy and no downtime.
100x faster queries and real-time diagnostics.
Problem: Redundant compute, storage and transfer layers, with ~20x event growth ahead.
What I did: Mapped data flows end to end, built a cost model around a 'cost per million events' KPI, and benchmarked direct ClickHouse ingestion, managed queues, self-hosted HA Nomad, optimized MySQL and DuckLake/Parquet on object storage.
A prioritized modernization roadmap built to absorb ~20x ingestion without linear cost growth.
Problem: No objective way to trust a production identity-resolution system.
What I did: Defined KPIs (identifiable and identified sessions, hard candidate and identification rates) and compared BFS and DSU (union-find) engines across 2-day to 7-month windows.
Verified output consistency before rollout.
Problem: Client-side tracking lost conversions and could not feed several ad platforms reliably.
What I did: Built an event collection service in Go, containerized and run on Nomad, that processes events and routes them to multiple destinations such as Meta and Google Ads.
The foundation of the company's tracking and attribution pipeline.
Problem: Shopify merchants needed analytical answers beyond what standard tools offer.
What I did: Designed and built an orchestrator from scratch that processes complex user queries, with OpenTelemetry tracing across the whole system.
Insight queries standard tooling could not answer, fully observable in production.
Problem: Recurring pipeline failures were being found by customers, not by us.
What I did: Centralized monitoring over infrastructure, application and data-quality signals, plus restart, rollback and database-recovery runbooks with post-recovery validation.
Recurring failures turned into alerts and repeatable procedures; MTTR down 65%.
I work remotely from Tunis with managers and a team based in Paris. Tunisia is on UTC+1 all year, so I overlap France's working day almost entirely.
I took on-call and overnight pager duty for production systems, so I know that remote reliability means alerts, runbooks and clear handoffs, not being in the room.
Post-mortems, runbooks, architecture decision notes and benchmark reports. I leave a trail someone else can pick up without a call.
Promoted to Technical Project Lead to run five-plus workstreams and coordinate priorities and deadlines, all remotely.
Italian citizenship: no visa or sponsorship needed to work in the EU.
ClickHouse · BigQuery · MySQL · PostgreSQL · DuckDB / DuckLake · Parquet & object storage · Message queues · ETL · Data quality
Go · Python · SQL · Bash · Rust · JavaScript · Java
GCP (Pub/Sub, Cloud Run, Cloud Functions, BigQuery, IAM, Cloud Monitoring) · Azure · Docker · Kubernetes · HashiCorp Nomad · Ansible
On-call · Incident response · Runbooks · Fluentd · Elasticsearch · Graylog · Grafana · Prometheus · OpenTelemetry
Jenkins · GitHub Actions · SonarQube · Git · TDD
Looking for a remote data engineer role with a European team.
khalilrezgui0@gmail.com