[1727] - Data Engineer

About the Role

We are seeking a Senior Data Engineer to join a 3-month remote project in a multicultural team. You will operate across both sides of data engineering: keeping data platforms reliable and performant, while also designing modern, event-driven data systems that power AI-enabled products and analytics use cases.

In this role, you will work across multiple projects, ranging from stabilizing and optimizing existing data stacks to designing new pipelines for real-time behavioral analytics, machine learning, and AI workloads. The ideal candidate is comfortable switching between operational excellence and greenfield architecture, depending on project needs.

Key Responsibilities

Data Platform Operations

• Monitor and maintain data ingestion and transformation pipelines to ensure reliability and data quality.

• Triage alerts, debug pipeline failures, and resolve production data issues efficiently.

• Tune warehouse and pipeline performance to improve reliability, scalability, and cost efficiency.

• Ensure scheduled jobs and dependencies run consistently and recover gracefully from failures.

Data Architecture & Pipeline Development

• Design and build new data infrastructure from scratch when required.

• Implement event-driven architectures, real-time data pipelines, and scalable data models.

• Develop data pipelines that support analytics, machine learning models, and AI agents.

• Balance short-term stability needs with long-term architectural improvements.

Collaboration & Communication

• Work independently once context is understood, owning problems end to end.

• Communicate clearly with both technical teammates and non-technical stakeholders.

• Ask the right questions before implementation to ensure alignment and impact.

• Contribute to a culture of reliability, ownership, and continuous improvement.

Required Qualifications

• 4+ years of experience in data engineering roles.

• Advanced proficiency in SQL and Python.

• Strong experience with cloud data warehouses such as Redshift, Snowflake, BigQuery, or similar.

• Hands-on experience with orchestration tools (Airflow, Dagster, Prefect, or equivalent).

• Experience building and maintaining ETL/ELT pipelines.

• Familiarity with data ingestion tools such as Fivetran, Segment, Stitch, or similar.

• Experience working in AWS environments, including S3, Lambda, and general cloud infrastructure.

• Experience with pipeline monitoring, alerting, and incident response.

• Proven ability to debug and resolve production data issues under pressure.

Preferred Qualifications

• Experience with event-driven architectures (Kafka, EventBridge, or similar).

• Familiarity with real-time data processing and streaming systems.

• Experience with PostgreSQL and platforms such as Supabase.

• Exposure to NoSQL databases (e.g., DynamoDB).

• Understanding of data modeling for analytics and machine learning use cases.

• Experience supporting ML/AI workloads, feature stores, or feature pipelines.

• Exposure to BI tools such as Looker, Metabase, or similar.

What We Value

• Autonomy and strong ownership mindset.

• Calm, structured problem-solving in production environments.

• Clear communication with technical and non-technical stakeholders.

• Ability to balance system stability with innovation.

• Curiosity, adaptability, and continuous learning.

About the Company

We are a technology-driven organization building data-intensive platforms and AI-enabled products through distributed teams. We focus on solving complex problems with reliable, scalable data systems, fostering a culture of ownership, technical excellence, and real-world impact.