Data Platform Engineer - Fintech Governance (Remote)

Cari Network; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

401(k) matching

Remote-first policy

Flexible PTO

Job summary

Cari Network is building a blockchain-based payments system and seeks a senior data engineer to own ingestion pipelines from transactional sources into the analytics platform.

You will collaborate on governance, data residency, and platform choices (AWS, Snowflake, Databricks), enforce a strictly derived analytics layer, and mentor junior engineers while shaping production-ready data infrastructure.

Qualifications

• 5–7 years of data engineering experience with hands-on pipeline design.
• Experience comparing AWS-native tooling, Snowflake, and Databricks with governance focus.
• Experience building data governance: access controls, audit logging, data lineage.
• Production experience with streaming or event-driven pipelines (Kafka/MSK).
• Strong written communication and ability to write design docs.

Responsibilities

• Own ingestion pipeline design from transactional/infrastructure into analytics platform.
• Contribute input to platform evaluation (AWS, Snowflake, Databricks) with governance focus.
• Define data governance practices: access controls, audit logging, lineage.
• Enforce boundary that analytics is derived from source of truth.
• Define data quality and reconciliation practices for downstream consumers.
• Write RFCs and design docs for ingestion and governance decisions.
• Define production-ready standards: monitoring, alerting, recovery.
• Mentor less-senior data engineers.

Skills

Data engineering

Communication

Mentoring

Tools

Kafka/MSK

PostgreSQL

Snowflake

Databricks

Terraform

AWS

Job description

Cari Network is building a blockchain-based payments system and seeks a senior data engineer to own ingestion pipelines from transactional sources into the analytics platform.

You will collaborate on governance, data residency, and platform choices (AWS, Snowflake, Databricks), enforce a strictly derived analytics layer, and mentor junior engineers while shaping production-ready data infrastructure.