Data Engineer

Addi

. Own and evolve the core data ingestion and transformation platform .

Posted 9/28/2026full-timeRemote • ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying data ingestion and transformation platforms, with a focus on high availability, data governance, and compliance. Proficient in building production-grade data pipelines and implementing data quality checks to support financial decision-making.

Highest-signal resume keywords

Data EngineeringData Pipeline DevelopmentDatabricksPySparkAirflow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationSchema EvolutionAutomated Data Quality ChecksMonitoring DashboardsCI/CD PipelinesPerformance TuningData ContractsAnomaly DetectionIncremental Processing

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

Delta LakeWorkflow OrchestrationGitUnity Catalog

Industry Keywords

FintechHigh-Growth StartupData GovernanceRBACAuditability

Tech Stack

Tools & technologies

AirflowPySparkUnity

About the role

Key responsibilities & impact

Own and evolve the core data ingestion and transformation platform
Design, deploy, and monitor mission-critical data pipelines with high availability and strict SLO/SLI performance
Lead migration to a unified ingestion framework with standardized CDC patterns, schema evolution, and automated data quality checks across Bronze, Silver, and Gold layers
Design monitoring dashboards, alerting systems, and runbooks for self-serve incident diagnosis and resolution
Enforce enterprise-wide data governance, RBAC, and data classification for security, auditability, and compliance
Create standard pipeline templates, CI/CD automated checks, and local testing utilities to improve developer productivity
Collaborate with Product, Analytics, Finance, and Operations to translate business needs into robust, accessible datasets
Optimize pipeline efficiency, automate manual processes, and introduce data engineering best practices
Support reliable real-time financial decisions for Risk, Lending, and Finance

Requirements

What you’ll need

4+ years in Data Engineering
Proven track record building and operating production-grade data pipelines, ideally within a high-growth startup or fintech environment
Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or a related technical field
Ability to design pragmatic systems with clear trade-offs, documented via Architectural Decision Records (ADRs)
Experience taking pipelines from concept and design through deployment, live monitoring, and post-production iteration
Strong hands-on experience with Databricks, PySpark, and Delta Lake across batch and streaming architectures
Experience using Airflow or similar workflow orchestration tools
Familiarity with Medallion architectures and incremental processing techniques such as CDC and merge patterns
Clean code, testing, CI/CD pipelines, performance tuning, and Git workflows including PRs and code reviews
Expertise implementing data quality checks, data contracts, and anomaly detection
Ability to build monitoring dashboards, alerting frameworks, and runbooks; improve MTTR and on-call response
Experience with fine-grained access control such as Unity Catalog, PII classification, DLP, and auditability
Ability to translate infrastructure decisions into business impact for Risk, Finance, Product, and Operations stakeholders

Benefits

Comp & perks

Generous salary
Equity in the company
Benefits that go beyond the basics to support your growth
Opportunity to shape company technology, strategy, culture, and values
High-impact growth opportunity
Work alongside a world-class team
Fast, transparent, and engaging hiring experience
Feedback provided regardless of hiring outcome