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Data Engineer (SQL) - Costa Rica

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Listed location: Remote
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What you’ll work on

Full posting
  • Build, transform, and process datasets to keep data accurate, reliable, and available for analytics and business decisions.

From the employer’s posting
Responsibilities: Build, transform, and process datasets to keep data accurate, reliable, and available for analytics and business decisions. Maintain high-quality data infrastructure supporting reporting, analytics, and operational insights, including pipeline ingestion (Fivetran, Kafka), transformation and modeling (dbt, Snowflake), and Level 1 support for pipeline failures, monitoring, and data quality. Qualifications and Skills

Tools in this posting

  • Python
  • SQL
  • dbt
  • Fivetran
  • Kafka
  • Snowflake
Source — Tool mentions in context
Job Summary The Data Engineer is an individual-contributor role that designs, builds, and maintains scalable data pipelines and analytical data models. The role works hands-on with our modern data stack — SQL, Snowflake, dbt, Fivetran, Kafka, and Python — to build reliable, efficient data solutions. This is an entry-level role that grows toward full ownership of the data engineering workload over time. Responsibilities:
- Strong SQL skills - Python for data pipelines and automation - Snowflake
Qualifications and Skills - Strong SQL skills - Python for data pipelines and automation
Responsibilities: Build, transform, and process datasets to keep data accurate, reliable, and available for analytics and business decisions. Maintain high-quality data infrastructure supporting reporting, analytics, and operational insights, including pipeline ingestion (Fivetran, Kafka), transformation and modeling (dbt, Snowflake), and Level 1 support for pipeline failures, monitoring, and data quality. Qualifications and Skills
- Snowflake - dbt - Fivetran
- dbt - Fivetran - Kafka
- Fivetran - Kafka - Data modeling
- Python for data pipelines and automation - Snowflake - dbt
This role adds capacity to the data engineering function and reduces key-person risk by developing an engineer who can independently own the data engineering workload — ingestion, streaming, transformation, and data quality. As that ownership grows, it frees senior capacity to focus on higher-leverage architecture and modeling work. Reliable, well-governed data is the foundation for ActiveProspect's reporting and decision-making. By keeping pipelines healthy and data trustworthy in Snowflake, this role directly supports the analytics and business teams that depend on accurate, timely data. Success looks like dependable data delivery, strong data quality, and faster resolution of issues through proactive monitoring and Level 1 support.

Job description

View original posting ↗

Data Engineer

Company Overview

ActiveProspect is on a mission to make consent-based marketing the best channel for online customer acquisition. We provide marketers the products they need to acquire qualified customers at scale. Our platform is trusted by thousands of companies engaged in direct-to-consumer marketing, helping them save wasted spend, comply with ever-changing regulations, and manage a constantly evolving partner landscape. Our flagship product, TrustedForm, is used to certify over 1 billion opt-in digital customer leads every year and is the gold standard for documenting prior express written consent for TCPA compliance.

Job Summary

The Data Engineer is an individual-contributor role that designs, builds, and maintains scalable data pipelines and analytical data models. The role works hands-on with our modern data stack — SQL, Snowflake, dbt, Fivetran, Kafka, and Python — to build reliable, efficient data solutions. This is an entry-level role that grows toward full ownership of the data engineering workload over time.

Responsibilities:

Build, transform, and process datasets to keep data accurate, reliable, and available for analytics and business decisions. Maintain high-quality data infrastructure supporting reporting, analytics, and operational insights, including pipeline ingestion (Fivetran, Kafka), transformation and modeling (dbt, Snowflake), and Level 1 support for pipeline failures, monitoring, and data quality.

Qualifications and Skills

  • Strong SQL skills
  • Python for data pipelines and automation
  • Snowflake
  • dbt
  • Fivetran
  • Kafka
  • Data modeling
  • ETL/ELT pipeline development
  • Data quality and governance
  • Monitoring and performance optimization

Reports to:

  • Data Architect

Organizational Impact

This role adds capacity to the data engineering function and reduces key-person risk by developing an engineer who can independently own the data engineering workload — ingestion, streaming, transformation, and data quality. As that ownership grows, it frees senior capacity to focus on higher-leverage architecture and modeling work.

Reliable, well-governed data is the foundation for ActiveProspect's reporting and decision-making. By keeping pipelines healthy and data trustworthy in Snowflake, this role directly supports the analytics and business teams that depend on accurate, timely data. Success looks like dependable data delivery, strong data quality, and faster resolution of issues through proactive monitoring and Level 1 support.


 

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Source & posting history

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Pay

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Location & working pattern

Remote

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Status in our records
Active
First seen by us
Jul 8, 2026
Recorded sightings
28
Last seen by us
Oct 1, 2026

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