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Addi is a leading fintech platform in Colombia serving 3.6M+ customers and 55,000+ merchants, offering Buy Now, Pay Later, banking solutions (deposits, payments, unsecured credit), and commerce services. The company has achieved profitability and secured regulatory approval to operate as a bank, backed by top-tier investors including Andreessen Horowitz, Goldman Sachs, and Union Square Ventures.
You will own Addi's marketing data platform, including pipelines and integrations connecting data to Braze, AppsFlyer, GTM, Marketplace, and the App. The role emphasizes using AI agents as the default working method to make marketing data reliable, efficient, and self-service for Marketing, Growth, and Marketplace teams.
Key responsibilities over a 9-month roadmap:
1. **Ramp-up (90 days)**: Map the marketing data platform end-to-end (sources, jobs, tables, integrations) by writing documentation usable by both people and AI agents. Identify pain points and deliver a prioritized roadmap.
2. **Reliability (Month 3)**: Add tests and alerts to critical marketing pipelines, achieving 99% on-time data delivery for key tables. Reduce data incidents by 50% and identify root causes of anomalies within 2 business days.
3. **Agentic Automation (Month 6)**: Ship 2+ AI agents or agentic workflows handling recurring marketing data work (audience/segment requests, data quality triage, documentation). Each must have 3+ active users, a runbook, and documented improvements within 6 weeks. Remove 50%+ of manual requests.
4. **Efficiency (Month 9)**: Reduce cost or runtime of main marketing pipelines by 30%+ by eliminating unused or duplicated tables and jobs.
5. **Governance**: Maintain a single marketing data catalog with owners and approval rules, ensuring all data sent to marketing tools comes from official pipelines.
You'll work with a world-class team in a high-growth fintech environment, directly impacting millions of customers' financial access and experience.
**Requirements:**
- Proven experience writing and debugging complex SQL without AI assistance: confident with joins at scale, window functions, CTEs, incremental logic; ability to identify incorrect query results and explain why; builds clean, reusable, testable, documented tables and datamarts.
- Track record building and operating ELT pipelines on modern data platforms: hands-on with dbt, Airflow or similar; Git and code review experience; proficiency with SQL warehouses, notebooks, scheduled jobs; understands catalog, schema, table, and permissions management; uses tests, monitoring, and alerts by default; comfortable with on-call incident response.
- Ability to automate and integrate with Python: builds scripts and API integrations others can run independently.
- Daily experience using coding agents (Claude Code, Codex, Cursor or similar) for real data work: writes specs before building, delegates multi-step tasks to agents, reviews results; can demonstrate before/after examples.
- Solid expertise building agents and agentic workflows others use: has built at least one agent/workflow chaining LLM calls with tools (SQL, APIs, MCP servers) with real users; understands failure modes, guardrails, and agent testing with real inputs.
- Demonstrated ability validating AI output: has caught plausible but incorrect AI work (e.g., SQL with bad joins) and added checks; knows when human review is required, especially for customer data sent to marketing tools.
- Track record writing documentation for people and agents: writes context, runbooks, READMEs, agent instructions, and data catalog entries enabling teammates or AI agents to maintain systems without the author.
- Proven ability translating business needs and owning outcomes in ambiguity: understands Marketing, Growth, and Marketplace needs; decides whether solutions are tables, pipelines, agents, or self-service tools; manages own backlog and ships without close direction; communicates clearly with technical and non-technical stakeholders; English fluency required.
**Desirable Qualifications:**
- Experience with marketing tools: CRM (Braze or similar), app attribution (AppsFlyer or similar), tag management (GTM).
- Reverse ETL or CDP experience.
- Advanced data platform experience: pipeline tools, Spark performance tuning, data platform certifications.
- LLM APIs, LiteLLM, or MCP server building experience.
- A/B testing and basic statistics.
- Data privacy knowledge (consent, opt-out, Habeas Data).
- AWS and fintech or regulated industry background.
