Principal data Engineer

About UsWe are building a next-generation data engineering platform designed to simplify complex data workflows, automate orchestration, and deliver high-performance pipelines at scale. Our stack includes Python, Apache Airflow, PySpark, and FastAPI, and we’re looking for passionate engineers who want to shape the future of data engineering. Role OverviewAs a Principal Data Engineer, you will play a critical role in designing and building core components of our data platform. This is a hands-on leadership role where you’ll drive architecture decisions, mentor engineers, and own complex data problems end-to-end. You’ll collaborate closely with product and platform teams to define scalable, reliable, and high-performance data systems. Key Responsibilities·      Design and build scalable, reusable data engineering components and frameworks using Python, Airflow, and PySpark.·      Lead the architecture of end-to-end data pipelines — from ingestion and transformation to orchestration and monitoring.·      Build and maintain FastAPI-based services to expose metadata, control plane, and developer APIs.·      Drive best practices in software engineering and data architecture (code quality, testing, CI/CD, performance).·      Mentor and guide a team of data and backend engineers.·      Collaborate with product managers, designers, and other engineers to deliver features on time and at high quality.·      Evaluate and introduce tools, frameworks, and technologies that improve the developer experience and platform scalability. RequirementsTechnical Skills:·      10+ years of experience in software or data engineering, including experience building large-scale data platforms or products.·      Expert-level Python skills with a strong software engineering background.·      Deep expertise in Apache Airflow (or similar orchestration tools) and PySpark (or distributed data processing frameworks).·      Strong understanding of API design and development using FastAPI or similar frameworks.·      Experience with data modeling, schema design, and working with large-scale data (TB/PB scale).·      Hands-on experience with cloud-native data platforms (AWS, GCP, or Azure).·      Familiarity with containerization (Docker), CI/CD pipelines, and infrastructure-as-code is a plus.Leadership & Communication:·      Proven track record in leading technical design discussions and making architecture decisions.·      Strong mentorship skills and the ability to drive a high-performing engineering culture.·      Excellent communication skills, both written and verbal, with the ability to convey complex ideas to both technical and non-technical stakeholders. Nice to Have·      Experience building developer tools or internal platforms.·      Exposure to modern data tools like dbt, Snowflake, Delta Lake, etc.·      Open-source contributions in data or backend engineering. What We Offer·      Opportunity to lead and shape a cutting-edge data platform from the ground up.·      Collaborative and product-minded engineering culture.·      Competitive compensation, equity, and benefits.·      Flexible remote/onsite working model.

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