Principal Data Engineer - Remote

Overview

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Data Engineer. In this role, you will lead the design and development of data architecture and pipelines, shaping the future of the data ecosystem. Your work will drive innovation in data pipelines, architecture, and cloud platforms, directly impacting insights and decision-making processes. Collaborating closely with teams across various functions, you will help create scalable solutions that improve business operations and analytics capabilities. This is a unique opportunity for someone passionate about solving complex challenges and mentoring a high-performing team.

In Short

• Lead and mentor a team of data engineers responsible for building and maintaining scalable data pipelines and infrastructure on AWS, Snowflake, and Azure.
• Architect and implement end-to-end data pipeline solutions, ensuring high performance, resilience, and cost efficiency across both batch and real-time data flows.
• Define and drive the long-term vision for data engineering in alignment with our partner's data platform strategy and analytics roadmap.
• Collaborate with analysts, data scientists, FinOps engineers, and product/engineering teams to translate business needs into reliable, scalable data solutions.
• Establish and enforce standards for data quality, governance, observability, and operational excellence.
• Design and optimize data models, ELT/ETL processes, and data architectures to support analytics, BI, and machine learning workloads.
• Implement best practices in CI/CD, testing frameworks, and deploying data pipelines.
• Leverage modern data integration tools such as Fivetran, Nexla, and Airflow for batch ingestion and transformation workflows.
• Apply AI-driven approaches for anomaly detection, pipeline optimization, and automation.
• Stay current with emerging trends in data engineering and proactively evolve the team’s capabilities and toolset.

Requirements

• 10+ years of experience in data engineering, with at least 3 years in a lead role.
• Demonstrated success in delivering large-scale, enterprise-grade data pipeline architectures and leading technical teams.
• Expertise with cloud data platforms; AWS and Azure experience is a strong plus.
• Proficiency in SQL, Python, and modern data modeling practices.
• Hands-on experience with batch and streaming frameworks (e.g., Spark, Kafka, Kinesis, Hadoop).
• Proven track record of building and maintaining real-time and batch data pipelines at scale.
• Deep understanding of ETL and ELT paradigms, including traditional ETL and modern ELT tools.
• Experience with data integration tools (Fivetran, Nexla, etc.) and orchestration platforms.
• Familiarity with Data Lakehouse architectures, data mesh concepts, and hybrid/multi-cloud strategies.
• Strong communication, leadership, and stakeholder management skills.
• Ability to drive scalable architecture decisions through platform systems design and modern engineering patterns.

Benefits

• Remote work flexibility.
• Opportunities for professional growth and development.
• Comprehensive benefits package, including health, wellness, and financial benefits.
• Culture of belonging and inclusivity.
• Competitive compensation, which may include bonuses and stock grants.