Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the development of intricate data platforms, cloud-native data services, enterprise integrations, and scalable data pipelines across various products and systems.

• Set engineering best practices for AI-assisted development, data engineering, data quality, observability, testing, security, and software reliability.

• Assess emerging data technologies, AI-driven engineering capabilities, and cloud services while facilitating technical adoption.

• Advocate for AI-assisted engineering tools, intelligent automation, and contemporary data engineering methodologies.

• Create scalable data architectures that balance maintainability, security, performance, scalability, reliability, and business goals.

• Direct the technical execution of complex data engineering projects and guide architectural decisions and implementation trade-offs.

• Design and enhance multi-tenant data platforms, REST APIs, ETL/ELT pipelines, event-driven data integrations, data warehouses, and cloud-native data services.

• Ensure that solutions adhere to standards for data quality, governance, testing, operational readiness, security, and compliance.

• Enhance data engineering automation, developer productivity, platform reliability, data quality, and delivery efficiency.

• Create reusable frameworks, data engineering standards, technical documentation, reference architectures, and tools.

• Identify systemic challenges in data engineering and implement long-term enhancements.

• Optimize AWS-based data platforms through automation, monitoring, observability, cost management, and performance tuning.

• Collaborate with Product, Engineering, Architecture, Infrastructure, Quality Engineering, DevEx, and technical leaders.

• Facilitate technical discussions, architecture evaluations, cross-team initiatives, and enterprise data integration efforts.

• Mentor Data Engineers through coaching, design reviews, code reviews, and knowledge sharing.

• Impact engineering decisions through modern data architecture, cloud-native methodologies, data governance, and operational excellence.

⛳️ Requirements

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related field, or an equivalent combination of education and experience.

• 5+ years of progressive experience in data engineering, backend software engineering, or cloud-native platform development.

• Advanced proficiency in Python and contemporary software engineering practices, including object-oriented programming, asynchronous programming, type hinting, and application architecture.

• Expert experience with SQLAlchemy ORM, Alembic migrations, PostgreSQL, relational database design, and query optimization.

• Experience in designing scalable REST APIs, distributed systems, enterprise data pipelines, and cloud-native applications.

• Strong expertise in designing and implementing ETL/ELT pipelines, data integration solutions, and enterprise data platforms.

• Proficient with AWS services, cloud-native architectures, Infrastructure as Code (Terraform or equivalent), CI/CD pipelines, observability, automation, and DevOps practices.

• Familiarity with AI-assisted software development tools and modern engineering methodologies.

• Capability to lead intricate technical projects, influence architectural decisions, and reconcile technical trade-offs with business objectives.

• Strong analytical, systems-thinking, and problem-solving skills.

• Excellent communication, collaboration, and technical mentoring abilities.

• Experience leading enterprise-scale data platform or cloud modernization projects across multiple teams.

• Expertise with Snowflake, contemporary data warehouses, lakehouse architectures, or large-scale analytics platforms.

• Experience in designing event-driven architectures, streaming platforms, or distributed data processing systems.

• Familiarity with Kubernetes, container orchestration, platform engineering, or Site Reliability Engineering practices.

• Experience in establishing engineering standards, reusable frameworks, shared developer tools, or data governance practices.

• Background in AI-assisted development, intelligent automation, machine learning pipelines, or AI-enabled data engineering.

• AWS, Snowflake, or other cloud and data engineering certifications.

• Experience contributing to enterprise architecture, technology strategy, or organizational engineering initiatives.

• Experience designing data platforms that support LLMs, vector databases, RAG, semantic search, or AI-powered applications.

🏝️ Benefits

• 4+ weeks of vacation.

• 13+ paid holidays.

• 12 weeks of fully paid parental leave for all parents.

• 401(k) with a 0.5:1 company match.

• Medical, dental, and vision plans.

• Company-paid life, short-term disability, and long-term disability insurance.

• Voluntary supplemental life, accident, and pet insurance.

• ClassLink Cares paid volunteer days.

• Tuition reimbursement for continued education.

• Coaching and internal programs supporting career and personal growth.

• Annual company retreats and team events.