Data Engineer

What’s the mission you’ll drive

Own and evolve the core data ingestion and transformation platform to deliver highly reliable, governed, and agile data architecture. You will serve as the engine that reduces technical friction, ensuring absolute data integrity so critical functions such as Risk, Lending, and Finance can make confident, real time financial decisions.

What you will do

• Own Core Data Pipelines: Lead the end-to-end design, deployment, and operational monitoring of mission-critical data pipelines to ensure high availability and strict SLO/SLI performance.

• Standardize Data Ingestion: Drive the migration to a unified ingestion framework, establishing standardized CDC patterns, schema evolution, and automated data quality checks across Bronze, Silver, and Gold layers.

• Build Self-Serve Observability: Design monitoring dashboards, alerting systems, and runbooks that enable engineering teams to diagnose and resolve data incidents independently.

• Implement Data Governance: Enforce enterprise-wide data governance, RBAC, and data classification to ensure security, auditability, and compliance across business domains.

• Boost Developer Productivity: Create standard pipeline templates, CI/CD automated checks, and local testing utilities to accelerate release cycles and improve engineering standards.

• Partner Cross-Functionally: Collaborate with Product, Analytics, Finance, and Operations teams to translate business needs into robust, accessible datasets.

• Drive Platform Excellence: Continuously optimize pipeline efficiency, automate manual processes, and introduce industry best practices across the data engineering ecosystem.

   

What we’re looking for

• 4+ years in Data Engineering: Proven track record building and operating production-grade data pipelines, ideally within a high-growth startup or fintech environment.

• Educational Background: Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or a related technical field.

• System Design & Pragmatism: Demonstrated ability to design pragmatic systems with clear trade-offs, documented via Architectural Decision Records (ADRs).

• End-to-End Ownership: Experience taking pipelines from concept and design through deployment, live monitoring, and post-production iteration.

• Modern Data Stack: Strong hands-on experience with Databricks, PySpark, and Delta Lake across both batch and streaming architectures.

• Workflow Orchestration: Solid experience using Airflow (or similar tools) for scheduling, backfills, retries, and managing SLAs/SLOs.

• Layered Architectures: Deep familiarity with Medallion architectures (Bronze/Silver/Gold) and incremental processing techniques (CDC, merge patterns).

• Software Engineering Fundamentals: High standard for clean code, testing, CI/CD pipelines, performance tuning, and Git workflows (PRs, code reviews).

• Data Quality Controls: Expertise implementing proactive data quality checks, data contracts, and anomaly detection to prevent silent failures.

• Observability & Incident Response: Proven ability to build monitoring dashboards, alerting frameworks, and runbooks that reduce MTTR and improve on-call response.

• Data Governance: Hands-on experience with fine-grained access control (e.g., Unity Catalog), PII classification, DLP, and auditability without sacrificing developer speed.

• Cross-Functional Communication: Ability to translate complex infrastructure decisions into business impact for stakeholders in Risk, Finance, Product, and Operations.

Why join us?

• Work on a problem that truly matters – We are redefining how people shop, pay, and bank in Colombia, breaking down financial barriers and empowering millions. Your work will directly impact customers' lives by creating more accessible, seamless, and fair financial services.

   

• Step 1: People Interview (30 min)

  A conversation with a recruiter to get to know you, your experience, and what you're looking for. We’ll also share more about Addi, our culture, and the role.

• Step 2: Initial Interview (60 min)

  A more in-depth conversation with the hiring manager, where we explore your skills, experience, and problem-solving approach. We want to understand how you think and work.

• Step 3: Take Home Challenge (5-6 days)

  Complete a simple take-home challenge within a 1-week window. With this technical challenge, we want to see your technical expertise solving a real-world problem. We expect that you invest 5 hours or less in developing a working solution.

• Step 4: Stakeholder interview (60 min)

  Meet with a Data Engineer and the Head of Data.

• Step 5: Co-Founder Interview (30 min)

  If there’s a strong match, you’ll have a final conversation with our Founder to align on expectations, cultural fit and ensure mutual excitement. From there, we’ll move quickly to an offer and discuss next steps.