Ismail Ouennich
I’m a senior data engineer who has spent the last 9 years building reliable, production-grade data pipelines and platforms for high-stakes analytics—especially on large-scale event data in the AWS ecosystem.
About
I’m a senior data engineer who has spent the last 9 years building reliable, production-grade data pipelines and platforms for high-stakes analytics—especially on large-scale event data in the AWS ecosystem. I’m used to owning end-to-end delivery, from ingestion and reconciliation to deduplication and automated data validation, so the metrics teams and executives rely on stay trustworthy.
I also enjoy modernizing engineering workflows with AI: I integrate LLM APIs and build agent-style workflows with guardrails, and I use AI-assisted development with tools like Claude and MCP to speed up verification and documentation while keeping quality firmly under engineer control. I’m comfortable working remotely across time zones, mentoring teammates, and making pragmatic first-principles trade-offs to balance cost, speed, and correctness.
- 10 years' experience
- Joined November 2025
Skills· 21
Languages
- EnglishFluent
- FrenchFluent
Industry experience
- Financial Services
- Healthcare
- Manufacturing
- Software & Internet
- Professional Services
- Media & Entertainment
- Other
- Government
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Work experience· 22 roles
Own reliable data delivery on a 100M+ MAU platform: multi-source ingestion and reconciliation across product events (Amplitude), billing (RevenueCat, Zuora) and an mParticle event pipeline. Built automated validation and reconciliation logic on log-level billing data to surface material errors in conversion metrics. Designed deduplication and metric-definition standards that keep metrics fixed and consistent. Write production SQL on petabyte-scale event data (Athena/Presto), using window functions, CTEs, partition-aware and shard-sampled queries tuned for cost and speed. Govern event taxonomy across 150+ event types in 3 projects, partnering with backend engineers across US/EU time zones.
Own subscription revenue and user-behaviour analytics on a consumer platform with 100M+ monthly active users. Build cohort and funnel analyses across trial-to-paid conversion, churn and MRR for senior stakeholders. Write complex multi-step SQL on petabyte-scale data using Athena/Presto (window functions, CTEs, large joins) and apply performance tuning and query optimisation. Traced a reconciliation gap across billing sources (RevenueCat, Zuora) that materially inflated reported conversion rates. Designed event-tracking governance across 150+ events, including deduplication and metric-definition documentation. Use AI-assisted workflows daily (prompt-driven SQL generation, automated insight summaries, and QA with Claude + MCP-based tooling).
Designed and ran a production Medallion lakehouse (Bronze/Silver/Gold) on Databricks with Delta Lake. Implemented partitioning and Z-ordering strategies, OPTIMIZE/VACUUM lifecycle management, and time travel for auditability. Authored PySpark and SQL transformation pipelines across multiple sources. Orchestrated workflows with Azure Data Factory and Databricks Workflows, including dependencies, scheduling, and failure handling. Served as technical lead with architecture decisions, code reviews, and mentoring, improving documentation and deployment standards. Implemented row-level security.
Education· 10
Certifications and awards· 15
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