Data Platform Engineer

About the role

The Data Platform Engineer will own critical parts of Paxos' data platform, from design through production operation. You will work on data ingestion, pipelines, streaming systems, data lakes, warehouses, and cloud infrastructure, collaborating with engineers across US and India time zones.

Key responsibilities

• Own data‑platform projects end‑to‑end: clarify the problem, evaluate alternatives, design, implement, roll out safely, document, and operate in production.
• Design and evolve reliable, scalable, secure, and cost‑effective systems for data ingestion, movement, storage, processing, and access.
• Build and improve batch and streaming pipelines and the platform capabilities that support them.
• Develop maintainable software, automation, infrastructure, and CI/CD workflows that make platform changes safer and more repeatable.
• Improve observability, performance, capacity management, incident response, recovery, and operational readiness across the platform.
• Incorporate security, access control, data protection, and governance requirements into platform design and delivery.
• Partner with engineering, analytics, security, compliance, and business stakeholders to understand needs, explain trade‑offs, and deliver pragmatic solutions.
• Evaluate and learn new technologies as platform needs evolve, applying sound engineering judgment.
• Use AI tools thoughtfully to accelerate research, design, implementation, testing, debugging, and documentation while critically validating output.
• Contribute to technical direction, design reviews, documentation, and mentoring across a small, high‑impact team.

Required profile

• Record of independently owning and delivering substantial production systems or platform work from definition through operation.
• Strong system‑design and problem‑solving skills, considering scale, reliability, failure modes, security, cost, maintainability, and migration trade‑offs.
• Deep production experience in at least one relevant area such as data pipelines, streaming, Kafka, data lakes, warehouses, time‑series databases, PostgreSQL, Kubernetes, or cloud infrastructure.
• Proficiency in at least one general‑purpose programming language and experience writing, testing, reviewing, and operating maintainable production code.
• Practical experience with automation, production operations, observability, incident response, and safe software or infrastructure delivery.
• Demonstrated learning agility: quickly become productive in unfamiliar technologies or domains without heavy direction.
• Clear written and verbal communication and ability to collaborate asynchronously across teams and time zones.
• Active, responsible use of AI tools in the engineering workflow, paired with strong validation and independent technical judgment.

Required skills

• Data pipelines and ingestion
• Distributed batch or stream processing (e.g., Spark)
• Messaging systems (Kafka)
• Data lakes or warehouses (Snowflake)
• Time‑series databases
• Relational databases (PostgreSQL)
• Kubernetes
• Cloud infrastructure (AWS)
• Infrastructure as code (Terraform/Terragrunt)
• Data transformation tools (dbt, Dagster)
• CI/CD workflows
• AI tools for development