Staff Data Engineer

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

📋 Description

• Oversee the technical design of extensive data systems, pipelines, and platform functionalities across various domains and engineering teams.

• Establish reusable architectural patterns, engineering standards, and best practices for data ingestion, transformation, orchestration, quality, and delivery.

• Develop scalable solutions utilizing Snowflake and associated cloud technologies, focusing on reliability, performance, maintainability, and cost-effectiveness.

• Collaborate with Data Engineering, Analytics Engineering, QA, Software Engineering, and business teams to convert complex requirements into viable technical solutions.

• Provide technical guidance for batch processing, CDC, streaming, API, and file-based data ingestion patterns.

• Drive the architecture for outbound data delivery via data sharing, APIs, SFTP, cross-cloud integrations, and other distribution methods.

• Support data products such as the Reporting Platform, DataBridge, AI-enabled applications, and MCP-based data services.

• Establish and enhance practices for observability, monitoring, automated testing, data quality, CI/CD, and operational readiness.

• Identify platform constraints, technical debt, and scalability issues, advocating for long-term solutions.

• Lead technical evaluations for significant initiatives and ensure architectural decisions align with enterprise standards.

• Mentor both senior and junior engineers through design assessments, technical direction, and knowledge exchange.

• Collaborate with engineering and business leadership on roadmap planning, architectural choices, technical trade-offs, and investment priorities.

• Assist in resolving complex production incidents and drive root-cause analysis and reliability enhancements.

• Assess emerging technologies and propose methods to enhance scalability, automation, developer productivity, or business capabilities.

⛳️ Requirements

• 8–12 years of experience in data engineering, software engineering, data platform engineering, or a related technical discipline.

• Extensive knowledge in data architecture, distributed data processing, data warehousing, and the design of large-scale data platforms.

• Proficient hands-on experience with Snowflake, covering architecture, performance optimization, security, governance, and cost management.

• Strong skills in data querying and coding proficiency in Python, Java, or similar programming languages.

• Significant experience in data modeling, ETL/ELT architecture, workflow orchestration, and performance optimization.

• Experience in designing and managing production-grade batch, streaming, or CDC-based data pipelines.

• Solid experience with cloud-based data platforms and contemporary data engineering architectures.

• Proven ability to create scalable technical solutions across diverse systems and domains.

• Experience in establishing engineering standards, reusable frameworks, or architectural patterns that are adopted by multiple teams.

• Strong understanding of data quality, observability, monitoring, CI/CD, and operational reliability.

• Demonstrated capacity to work independently on highly ambiguous and complex technical challenges.

• Experience mentoring engineers and influencing technical decisions without direct managerial authority.

• Excellent communication skills, capable of articulating complex technical concepts, trade-offs, and recommendations to both technical and non-technical stakeholders.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.

• Preferred: experience with AWS data services, distributed processing technologies, and event-driven architectures.

• Preferred: experience with Kafka, Debezium, Spark/PySpark, Airflow, or similar platforms.

• Preferred: experience designing external data sharing and delivery solutions across Snowflake, APIs, SFTP, and cross-cloud environments.

• Preferred: background in fintech, payments, commerce, financial services, or other regulated environments.

• Preferred: familiarity with AI/ML data architectures, AI-enabled applications, agentic workflows, or MCP-based integrations.

• Preferred: experience crafting platforms or frameworks that facilitate self-service data engineering or workflow automation.

• Preferred: expertise in governance, lineage, metadata management, access controls, and secure data-sharing practices.

• Preferred: experience leading modernization, migration, or platform transformation projects.

• Preferred: Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.

🏝️ Benefits

• Bonus programs.

• 401(k) match.

• Employee Stock Purchase Program (ESPP).

• HSA and FSA options.

• Financial wellness resources and employee discount programs.

• Medical, dental, and vision coverage.

• Mental health support for employees and dependents through Lyra Health.

• Family planning and women’s health benefits through Carrot.

• Gym membership reimbursement and virtual wellness programs (including yoga).

• 3 weeks PTO to start, with unlimited PTO after the first year.

• Education expense reimbursement.

• Leadership development programs.

• Certified Payments Professional (CPP) certification support.