Senior Data Platform Engineer (Remote - Namer) at Jobgether

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

18 Jan, 26

Salary

0.0

Posted On

20 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL Processes, Data Lakehouse Architecture, Python, SQL, Cloud-Native Technologies, Docker, Kubernetes, Relational Databases, Transformation Layers, Airflow, Airbyte, Kafka, Distributed Systems, DevOps, Infrastructure as Code

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Platform Engineer in North America. 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. Accountabilities: 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. 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. 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. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 The top 3 candidates with the highest match are automatically shortlisted. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong candidate is overlooked. The process is transparent, skills-based, and unbiased, focusing solely on your fit for the role. Once the shortlist is completed, it is shared with the hiring company, who then determines next steps such as interviews or additional assessments. Thank you for your interest! #LI-CL1

Responsibilities

Design and implement ETL processes to deliver data to stakeholders while maintaining and enhancing the data lakehouse architecture. Collaborate with cross-functional teams to address data flow and reporting requirements.