Staff Data Engineer

Job Description:

• Lead the technical design of large-scale data systems, pipelines, and platform capabilities across multiple domains and engineering teams
• Define reusable architecture patterns, engineering standards, and best practices for ingestion, transformation, orchestration, data quality, and data delivery
• Design scalable solutions across Snowflake and supporting cloud technologies, emphasizing reliability, performance, maintainability, and cost efficiency
• Partner with Data Engineering, Analytics Engineering, QA, Software Engineering, and business teams to translate complex requirements into sustainable technical solutions
• Provide technical leadership for batch, CDC, streaming, API, and file-based data ingestion patterns
• Drive architecture for outbound data delivery through data sharing, APIs, SFTP, cross-cloud integrations, and other distribution mechanisms
• Support data products including Reporting Platform, DataBridge, AI-enabled applications, and MCP-based data services
• Establish and improve observability, monitoring, automated testing, data quality, CI/CD, and operational readiness practices
• Identify platform limitations, technical debt, and scalability risks, driving long-term solutions
• Lead technical reviews for high-impact initiatives and align architectural decisions with enterprise standards
• Mentor senior and junior engineers through design reviews, technical guidance, and knowledge sharing
• Partner with engineering and business leadership on roadmap planning, architecture decisions, technical tradeoffs, and investment priorities
• Support complex production incidents and drive root-cause resolution and reliability improvements
• Evaluate emerging technologies and introduce approaches that improve 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 field
• Deep expertise in data architecture, distributed data processing, data warehousing, and large-scale data platform design
• Strong hands-on experience with Snowflake, including architecture, performance optimization, security, governance, and cost management
• Strong data querying skills and coding proficiency in Python, Java, or similar programming languages
• Strong experience with data modeling, ETL/ELT architecture, workflow orchestration, and performance optimization
• Experience designing and operating production-grade batch, streaming, or CDC-based data pipelines
• Strong experience with cloud-based data platforms and modern data engineering architectures
• Demonstrated ability to design scalable technical solutions across multiple systems and domains
• Experience establishing engineering standards, reusable frameworks, or architecture patterns adopted by multiple teams
• Strong understanding of data quality, observability, monitoring, CI/CD, and operational reliability
• Demonstrated ability to operate independently on highly ambiguous and complex technical problems
• Experience mentoring engineers and influencing technical decisions without direct management authority
• Strong communication skills with the ability to explain complex technical concepts, tradeoffs, and recommendations to 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: experience with fintech, payments, commerce, financial services, or other highly regulated environments
• Preferred: familiarity with AI/ML data architectures, AI-enabled applications, agentic workflows, or MCP-based integrations
• Preferred: experience designing platforms or frameworks enabling self-service data engineering or workflow automation
• Preferred: experience with governance, lineage, metadata management, access controls, and secure data-sharing patterns
• Preferred: experience leading modernization, migration, or platform transformation initiatives
• Preferred: Master’s degree in Computer Science, Engineering, Data Science, or a related technical discipline

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 year one
• Education expense reimbursement
• Leadership development programs
• Certified Payments Professional (CPP) certification support