Senior Staff Software Engineer, Data

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Define and own the end-to-end architecture strategy for data and analytics, including scalable batch, streaming, and real-time systems.
• Lead the transformation toward a modern Data Platform using approaches such as lakehouse, data mesh, real-time analytics, self-service data access, and reusable data products.
• Design and prototype critical platform components while writing production-quality code for complex and high-impact areas.
• Establish standards for data modeling, semantic layers, reporting, metadata, lineage, governance, and data quality.
• Build scalable infrastructure for structured and unstructured data, including ingestion, transformation, APIs, vector stores, embeddings, retrieval systems, and RAG-ready architectures.
• Develop "Data for Agents" capabilities that provide LLMs and AI agents with reliable, well-structured, governed, and discoverable enterprise data.
• Partner with AI, product, and engineering teams on training datasets, feature stores, production inference pipelines, and agentic ETL/ELT workflows.
• Ensure platform reliability, availability, observability, security, disaster recovery readiness, performance, and cost efficiency.
• Support analytics and business intelligence by developing scalable models and enabling trustworthy, performant, and accessible insights.
• Mentor senior engineers, analytics engineers, and data scientists while serving as a senior technical authority for data and analytics.
• Establish SLAs/SLOs, monitoring, alerting, incident response, capacity planning, and operational standards for the growing data ecosystem.
• Translate business needs into scalable technical solutions and influence product and engineering roadmaps through data expertise.
• Champion pragmatic AI adoption and outcome-driven innovation across the organization.

Requirements:

• Advanced degree in Computer Science, Engineering, or a related field.
• 15+ years of experience in data engineering, analytics engineering, data platforms, or closely related roles.
• Proven experience architecting and scaling large data and analytics systems in cloud environments.
• Deep expertise in data modeling for analytics, including dimensional modeling, star/snowflake schemas, Data Vault, and semantic layers.
• Advanced SQL skills and strong proficiency in Python, Scala, or Java.
• Hands-on experience with modern data stacks and cloud data services across AWS, Azure, or GCP.
• Strong knowledge of batch, streaming, and real-time architectures, with expertise in frameworks such as Spark, Flink, or Beam.
• Experience designing semantic layers or metrics stores using technologies such as dbt or Cube, particularly for making data accessible to AI and agentic systems.
• Experience building reporting and business intelligence solutions at scale, with familiarity with tools such as Looker, Tableau, or Power BI.
• Strong understanding of data governance, lineage, metadata, privacy, security, access controls, and auditability.
• Ability to operate effectively at both executive and deeply technical levels, with strong communication, collaboration, and technical leadership skills.
• Experience supporting AI/ML pipelines, feature engineering, real-time analytics, event-driven architectures, experimentation platforms, or product analytics is a plus.
• Experience in high-growth SaaS or data-intensive environments is also desirable.

Benefits:

• Base salary, equity, and a comprehensive benefits package.
• U.S. base salary range of $235,000–$285,000 USD, with actual compensation determined by experience, skills, location, and applicable local requirements.
• Health, dental, and vision coverage for employees and their families.
• Life insurance and mental wellness coverage.
• Fertility and growing-family support.
• Flexible time off in addition to company-paid holidays.
• Paid family leave, medical leave, and bereavement leave.
• Retirement savings plans.
• Allowance to customize home-office and technology equipment.
• Annual professional development stipend.
• Remote work environment.