Staff Data Engineer, Full Time

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

📋 Description

• Spearhead the design and practical implementation of scalable batch and near-real-time ETL/ELT pipelines along with data platform services.

• Establish integration patterns for databases, APIs, applications, CDC/event streams, and external sources across the enterprise data platform.

• Create reusable, governed data models, curated data products, and semantic-ready datasets for analytics, reporting, AI/ML, and operational applications.

• Tackle complex transformation and processing challenges utilizing Python, SQL, Snowflake, and distributed data technologies.

• Drive architectural decisions focused on scalability, availability, resiliency, performance, maintainability, and cost-effectiveness.

• Define reusable frameworks, libraries, reference architectures, and engineering patterns for data engineering teams.

• Advance automated testing, CI/CD, Infrastructure as Code, and DataOps standards.

• Implement observability, data freshness, service-level objectives, alerting, and automated recovery for critical data pipelines.

• Lead the resolution of high-impact production issues and conduct cross-system root-cause analysis.

• Enhance Snowflake and cloud compute efficiency, query performance, storage, and operating costs.

• Set technical standards for data quality, validation, lineage, reconciliation, and reliable data delivery.

• Collaborate with Data Architecture, Governance, and Security teams on discoverable, governed, reusable data assets and access patterns.

• Design healthcare data solutions that incorporate privacy, security, and compliance requirements from the outset.

• Act as a technical authority for design reviews, architectural decisions, code quality, and engineering best practices.

• Mentor Senior and other Data Engineers through design guidance, pairing, code reviews, and sharing knowledge.

• Collaborate with Data Scientists and Machine Learning Engineers on feature pipelines, ML-ready datasets, and governed data access for Generative AI and agentic applications.

• Convert ambiguous product and business requirements into architecture, phased delivery plans, and measurable technical outcomes.

• Effectively communicate architectural decisions, trade-offs, risks, and operational practices to both technical and non-technical stakeholders.

⛳️ Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical discipline.

• Over 8 years of experience in building and maintaining production-grade data platforms.

• Proven track record of ownership over complex systems or cross-team technical initiatives.

• Expert-level proficiency in Python and SQL.

• Strong skills in software design, testing, debugging, and code review methodologies.

• Extensive hands-on experience with Snowflake, focusing on data modeling, query optimization, performance, and cost management.

• Experience in architecting CDC, Kafka, Flink, or similar distributed event and streaming solutions.

• Strong background with AWS, including S3, Lambda, Glue, Kinesis, or equivalent cloud services.

• Proven experience in designing high-volume batch and near-real-time ETL/ELT architectures and reusable analytical data models.

• Familiarity with orchestration technologies such as Airflow or equivalent platforms.

• Proven experience in establishing CI/CD, Git-based workflows, automated testing, and Infrastructure as Code practices.

• Strong knowledge of data quality, governance, security, observability, production operations, and reliability engineering.

• Ability to lead technical decisions across teams, mentor engineers, and communicate trade-offs effectively.

• Hands-on, full-stack mindset with a willingness to take ownership of complex challenges from start to finish.

• Preferred: Experience with dbt and dimensional modeling or semantic-layer design.

• Preferred: Experience using AI-assisted development tools responsibly.

• Preferred: Experience supporting Machine Learning, Generative AI, feature engineering, and AI-ready data access patterns.

• Preferred: Familiarity with Docker, Kubernetes, Terraform, or CloudFormation.

• Preferred: Experience with metadata management, data catalogs, lineage, data observability, and governance of data products.

• Preferred: Background in Healthcare, HealthTech, SaaS, or other regulated industries.

🏝️ Benefits

• Comprehensive Medical, Dental/Orthodontia, and Vision coverage starting from the first day of employment.

• Eligibility for synthetic ownership after one year of service, with financial rewards linked to company performance.

• Employee Assistance Program that includes counseling, legal resolution, financial education, pet adoption assistance, and identity theft and fraud resolution.

• Flexible work scheduling options.

• Generous paid time off (PTO) that increases with milestones.

• Opportunities for career development and learning programs.

• Team-building events, family company picnics, and holiday celebrations.

• Quarterly bonuses.

• 401(k) retirement plan with employer matching contributions.

• Option to work remotely or from an office.