I'm Abed Maatalla, freelance Python, data and backend engineer

Ten-plus years building and scaling production systems in startup and enterprise environments. Core depth in Python and Django, data pipelines, PostgreSQL-heavy services, and performance under load: SQL, APIs, batch and async workloads.

Works at system level: framing architecture and trade-offs, guiding technical decisions across teams, and keeping performance, reliability and cost coherent as usage grows, rather than optimizing single services after the fact.

Trusted partner to product, UX and platform teams, regularly consulted on roadmap and integration choices beyond immediate feature ownership. Hands-on when it matters: CI/CD, automated tests, observability and production profiling during incidents or bottlenecks.

• Performance and reliability of data-intensive services on paths the product depends on. Other teams rely on those surfaces staying healthy as load shifts.
• Resolution of high-impact production issues touching user-visible flows, downstream reporting or cost.
• Architecture decisions that balance scalability, delivery speed and maintainability, with incremental rollout preferred over big-bang changes when it reduces risk.
• Latency, throughput and cost under growing traffic and data, improved through evidence: query plans, caching, pipeline design.
• Long-term evolution of the platform: observability, safer SQL and data paths, platform hygiene, not only short-term fixes.

• Scaled a traceability SaaS backend from about 40 to 700+ B2B clients Database and reporting performance held as analytics load grew. CodaBene
• Took the same platform from proof of concept to sustained production Monitoring, dashboards and automated reporting first; then autoscaling, CI/CD, Docker and Elasticsearch as constraints evolved. CodaBene
• Shipped substantial SQL and pipeline optimizations on large-scale, Oracle-backed product work Measurable gains on heavyweight queries and a safer path for evolution. Oracle
• Removed a costly Ext JS dependency Weighed vendor cost, maintenance and integration risk; lowered ongoing spend and simplified the path forward. Oracle
• Remediated a finance-automation stack on Django, Celery and Redis Bottlenecks and high-impact queries removed within a short engagement. ScaleXP

• Sets and raises expectations for testing, CI/CD and maintainability in codebases that must change safely over time.
• Mentors engineers and influences design decisions outside personal feature ownership.
• Bridges engineering, product, UX and non-technical stakeholders; translates constraints into bounded technical plans.
• Pragmatic architecture: no over-engineering, still enabling scale and clear service boundaries.
• When ambiguity is high, leads with explicit trade-offs (performance, cost, timeline) and documents the rationale for the team.

You are buying problem resolution and risk reduction, not generic dev hours. Strongest fit when a backend is already under pressure or trending toward breakage: latency spikes, throughput ceilings, noisy errors, creeping infrastructure cost, or an architecture that slows the whole team.

Short-to-mid term work, typically 2–12 weeks, on production backends: decisive scoping, quick time to first insight, and incremental delivery you can observe in metrics.

• Rapid diagnosis and resolution of production bottlenecks
• API and data architecture for products moving past their first scaling wall
• Stabilization under load: latency, error budgets, reliability, runaway cost
• Prototype to production-ready backend: guardrails, observability, safer change

• Performance audit across databases, APIs, pipelines and hotspots in production traces
• Fixing live latency or throughput regressions without guesswork
• Designing or refactoring APIs and service boundaries for scalability and team velocity
• Getting a stack ready for the next step in traffic or data volume
• Senior backend ownership during high-stakes delivery

• Ramps with minimal hand-holding and gets to a credible map of failure modes quickly.
• Comfortable when requirements are fuzzy or timelines are tense; defaults to small, verifiable slices of work.
• Pushes incremental gains early, then chains them into durable fixes.
• Direct, pragmatic updates for engineering leads and stakeholders. No needless ceremony.

• Computer Science degree.
• AI and ML certifications: O'Reilly, LinkedIn Learning, PMI, Oracle OCI AI Foundations.
• IELTS B2 (English), August 2019.

Trophées LSA and ESSEC-linked recognition for contributions at CodaBene: external validation for production systems that scaled with real business growth and usage constraints. Announcements: LSA, ESSEC, commerce responsable.

Full-time. Senior backend or technical-lead IC roles where I own critical system outcomes, influence technical direction across teams, and stay hands-on in production, from architecture through delivery, profiling and incident hardening.

Freelance and consulting. Engagements focused on performance, scalability and production reliability, from short diagnostics and fixes through longer uplift work. senior@abedmaatalla.me