Senior Data Platform Engineer (Remote - Namer)

Jobgether

65d

About The Position

We are seeking a highly skilled Senior Data Platform Engineer to design, build, and maintain scalable data infrastructure that supports complex, high-volume financial transactions and analytics. This role involves managing and evolving a modern data lakehouse architecture, ensuring efficient data ingestion, transformation, and delivery for internal teams and external partners. You will collaborate with cross-functional stakeholders across product, operations, and engineering, driving data initiatives that impact decision-making and product performance. The ideal candidate thrives in a fast-paced, distributed environment, brings deep technical expertise in data engineering, and is passionate about building robust, scalable systems. This is an opportunity to influence the platform’s data strategy and make a measurable impact on the organization’s growth.

Requirements

• 7+ years of experience in data engineering, including 2+ years building scalable, low-latency data platforms handling over 100M events/day.
• Proficiency in Python and SQL, with strong programming skills.
• Experience with cloud-native technologies such as Docker, Kubernetes, and Helm.
• Hands-on experience with relational databases and building transformation layers (e.g., dbt).
• Familiarity with ETL tools such as Airflow and Airbyte, and streaming systems like Kafka.
• Knowledge of distributed systems, storage, transactions, and query processing.
• Exposure to infrastructure, DevOps, and Infrastructure as Code (IaaC) practices.
• Ability to work independently in a fast-paced, remote, and distributed environment.
• Strong problem-solving skills, with the ability to adapt solutions to evolving business requirements.

Responsibilities

• Design and implement forward and reverse ETL processes to deliver data to relevant stakeholders.
• Develop scalable transformation patterns to ensure consistent integrations with BI tools across multiple business areas.
• Maintain and enhance the data lakehouse architecture to support growing volumes of transactional, operational, and third-party data.
• Collaborate with product, operations, sales, and marketing teams to address data flow and reporting requirements.
• Monitor, operate, and troubleshoot production systems, ensuring high availability and performance.
• Contribute to data experimentation, cataloging, and monitoring practices to maintain data quality and observability.

Benefits

• Competitive salary and equity/stock options.
• Comprehensive health benefits.
• One-time new hire home-office setup allowance (USD $500).
• Monthly stipend for home-office expenses (USD $150).
• Fully remote work with a globally distributed team.
• Inclusive and diverse workplace, fostering professional growth and collaboration.

What This Job Offers

• Career Level: Senior
• Number of Employees: 11-50 employees