Backend engineer with 10+ years building and scaling production systems across startup and enterprise environments. core depth in Python / Django, data pipelines, PostgreSQL-heavy services, and performance under load (SQL, APIs, batch/async workloads).

Works at system level: framing architecture and trade-offs, guiding technical decisions across teams, and keeping performance, reliability, and cost efficiency coherent as usage and datasets grow—not only optimizing single services after the fact.

Proven ability to stabilize and evolve complex systems under production pressure while aligning engineering with product and business constraints.

Trusted partner to product, UX, and platform teams; regularly consulted on roadmap and integration choices beyond immediate feature ownership. Hands-on IC: CI/CD, automated tests, observability, and production profiling when incidents or bottlenecks emerge. Open to focused consulting where the mandate is measurable improvement on live systems—clear scope and outcomes, not commodity staffing.

• Owned performance and reliability of data-intensive services on paths the product depended on—others relied on those surfaces staying healthy as load shifted.
• Led resolution of high-impact production issues affecting user-visible flows, downstream reporting, or cost.
• Drove architectural decisions balancing scalability, delivery speed, and maintainability; favors incremental rollout when it reduced risk vs “big bang” changes.
• Improved latency, throughput, or cost under growing traffic and data constraints with evidence-led changes (query plans, caching, pipeline design).
• Contributed to long-term evolution—observability, safer SQL/data paths, platform hygiene—not only short-term fixes.

• Owned scaling of a traceability SaaS backend from ~40 to 700+ B2B clients while preserving strong database and reporting performance under analytics load (CodaBene).
• Defined and shipped substantial SQL and pipeline optimizations on large-scale Oracle-backed product work—measurable gains on heavyweight queries and safer evolution (Oracle).
• Removed a costly EXT.js dependency after weighing vendor cost, maintenance, and integration risk—lowered ongoing spend and simplified the path forward (Oracle).
• Owned production remediation on a finance-automation Django/Celery/Redis stack—bottlenecks and high-impact queries removed on a short engagement (ScaleXP).
• Took the platform from POC to sustained production: monitoring, dashboards, automated reporting, then autoscaling, CI/CD, Docker, and Elasticsearch as constraints evolved (CodaBene).

• 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.
• Acts as a bridge between engineering, product, UX, and non-technical stakeholders—translates constraints into bounded technical plans.
• Advocates pragmatic architecture: avoid over-engineering while still enabling scale and clear service boundaries.
• When ambiguity is high, leads with explicit trade-offs (performance vs cost vs timeline) and documents the rationale for the team.

Consulting stance: you are buying problem resolution and risk reduction, not generic dev hours. Strong fit when a backend is already under pressure or trending toward breakage—latency spikes, throughput ceilings, noisy errors, creeping infra cost, or architecture that slows the whole team—and you need someone who maps the system quickly and implements backends that hold up under real constraints.

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.

• Engagements centred on backend systems, performance, and scalability
• 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: 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
• Boosting execution during high-stakes delivery with senior backend ownership

• Ramps with minimal hand-holding—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/ML certifications (O'Reilly, LinkedIn Learning, PMI, Oracle OCI AI Foundations).
• IELTS B2 (English), Aug 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, not hypotheticals. 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—architecture through delivery, profiling, and incident hardening.

Freelance / consulting: available for engagements focused on performance, scalability, and production reliability—from short diagnostics and fixes through longer uplift work. contact@abedmaatalla.me