Senior Data Engineer

Role Description

We’re looking for a Senior Data Engineer to become the first key technical owner of Cari’s analytical data foundation. You will design the ingestion and governance layer that transforms data from our transactional systems into a reliable analytical platform for compliance, reporting, and future analytics use cases. Since there is no existing data lake or warehouse, this is a hands-on, greenfield opportunity to establish the pipelines, architecture, and governance practices from the ground up.

Engineering leadership is currently evaluating AWS-native tooling, Snowflake, and Databricks. You will contribute directly to that decision, with particular focus on governance, compliance, data residency, and long-term operational fit.

This role is ideal for someone who can independently own a technical domain, make well-reasoned architectural decisions, and build production-ready systems in an early-stage environment.

What You’ll Do

• Design and own ingestion pipelines from PostgreSQL and Kafka/AWS MSK into Cari’s analytical platform.
• Define clear boundaries around which data is replicated, transformed, or derived.
• Provide technical input into the evaluation of AWS-native tooling, Snowflake, and Databricks.
• Assess platform tradeoffs involving governance, compliance, auditability, data residency, and operational complexity.
• Establish data governance practices, including access controls, audit logging, data lineage, and traceability.
• Ensure the analytical platform remains strictly derived from Cari’s transactional PostgreSQL source of truth.
• Prevent the analytical layer from becoming a shadow system of record or a path back into live transaction processing.
• Define data quality, validation, and reconciliation processes for compliance reporting, dashboards, and future analytical use cases.
• Establish production standards for pipeline monitoring, alerting, observability, failure recovery, and operational ownership.
• Write RFCs, architecture proposals, and design documentation that engineers and non-data stakeholders can act on.
• Mentor less-experienced data engineers as the data function grows.

Qualifications

• 5–7+ years of professional data engineering experience.
• Hands-on experience designing and building data pipelines, rather than only maintaining an established platform.
• Production experience ingesting data from transactional databases such as PostgreSQL.
• Production experience with Kafka, AWS MSK, or comparable streaming and event-driven technologies.
• Experience establishing data governance practices, including access control, audit logging, and data lineage.
• Working knowledge of AWS-native data tooling, Snowflake, and Databricks, including their governance and compliance tradeoffs.
• Strong understanding of transactional systems of record and how to keep analytical platforms strictly downstream and derived.
• Experience defining data quality, reconciliation, and reliability standards for production pipelines.
• Strong written communication skills, including experience producing RFCs and technical design documents.
• Ability to independently own a technical domain in an early-stage environment without an established playbook.
• Must be authorized to work in the United States.

Nice to Have

• Experience in fintech, payments, banking, healthcare, or another regulated industry.
• Experience working with data governance requirements carrying contractual or regulatory significance.
• Familiarity with blockchain or on-chain data, including transaction histories and event logs.
• Experience with SOC 2, data residency requirements, or similar compliance frameworks.
• Familiarity with Terraform or comparable infrastructure-as-code tooling.
• Previous experience mentoring data engineers or helping build a data platform function.

Benefits

• Competitive base salary, bonus, and equity.
• Medical, dental, and vision coverage.
• 401(k) with employer matching.
• Flexible paid time off.
• Remote-first working environment.
• The opportunity to build a critical data platform from the ground up and influence foundational technology decisions.