Senior Data Engineer

Summary

Join Encora as a Senior Data Engineer and play a key role in building and maintaining our data stack, from ingestion to modeling to warehouse optimization. Collaborate with data scientists, backend engineers, and stakeholders to ensure data is clean, reliable, and actionable. Build and maintain scalable data pipelines, implement ETL/ELT workflows using Python and SQL, and design data models in relational and non-relational environments. Maintain and optimize our cloud-based data warehouse, implement data quality checks, and help productionize ML model inputs/outputs. Monitor data infrastructure performance, ensure secure data handling, and document data flows. This remote position is available in Costa Rica, Colombia, Bolivia, Peru, and Argentina.

Requirements

• Bachelor’s degree in computer science, software engineering, or a related field
• Have 5+ years of data engineering experience in production environments
• Are proficient in Python and SQL, with experience in workflow orchestration (Step Functions, Airflow, Dagster, etc)
• Have hands-on experience with Spark, dbt, or similar tools for scalable transformations
• Are comfortable with cloud-native tooling – especially AWS services like S3, Lambda, RDS, and Glue
• Understand how to model and structure data for analytics, forecasting, and reporting
• Care deeply about data quality, testing, and long-term maintainability of pipelines
• Can work independently on scoped projects and communicate clearly across time zones
• Design, build, and manage data pipelines and ETL workflows
• Develop and maintain core data models, schemas, and warehouse structures
• Optimize data systems for scalability, reliability, and performance
• Support downstream consumers including ML pipelines, dashboards, and internal APIs

Responsibilities

• Build and maintain scalable pipelines for ingesting and transforming data from diverse sources
• Collaborate with product, data science, and engineering to define and prioritize data requirements
• Implement robust ETL/ELT workflows using Python, SQL, and workflow orchestration tools
• Design and evolve data models in relational (PostgreSQL) and non-relational environments
• Maintain and optimize our cloud-based data warehouse (e.g. Redshift, Snowflake, or equivalent)
• Implement data quality checks, monitoring, and validation logic to ensure trusted outputs
• Help productionize ML model inputs/outputs and support reproducible experimentation
• Monitor and improve performance of data infrastructure with observability and alerting
• Ensure secure handling of sensitive data and compliance with relevant data policies
• Document data flows, architecture, and transformation logic for team transparency

Preferred Qualifications

• Experience working in a modern data stack with tools like dbt, Snowflake, or Fivetran
• Exposure to production ML workflows or feature engineering pipelines
• Familiarity with infrastructure-as-code tools (Terraform, Pulumi) or containerized environments (Docker)
• Background in real estate, pricing, or time-series forecasting

Benefits

Remote work