Data Engineer

• Architects, deploys, and maintains production-grade Python microservices, serverless components (AWS Lambda), batch workers, web services, and shared core libraries across the analytics ecosystem
• Engineers RESTful interfaces and application integrations to expose dataset capabilities to platform applications, encompassing secure object storage exchange, query orchestration, automated report delivery, and embedded analytics infrastructure
• Constructs backend infrastructure powering AI analytics solutions, incorporating LLM and natural language query translation engines like Snowflake Cortex, controlling dialog state, guaranteeing multi-tenant data isolation before execution, and optimizing throughput and resource utilization
• Authors clean, resilient codebase backed by comprehensive test suites while directing GitHub Actions continuous integration and continuous deployment pipelines for automated compilation, verification, security inspection, and production releases
• Safeguards system configuration and secrets using key-pair authentication, parameter management, and service credentials while proactively updating software dependencies based on vulnerability scanning metrics
• Data Engineering
• Constructs and manages ingestion and transformation workflows utilizing Airflow, AWS Glue, Spark, and Snowflake dynamic tables to feed multi-tier lakehouse environments from diverse sources
• Engineers automated data cleansing and enrichment routines integrating machine learning models and record reconciliation methods, while safely executing massive historical data re-processing
• Architects robust multi-tenant security frameworks in Snowflake employing row-level policies, secure functions, and isolated access controls across global cloud infrastructure regions
• Implements metadata-driven automation to dynamically generate client-specific semantic layers from templates, incorporating state tracking, automated recovery, and version rollbacks
• Executes data governance protocols and privacy compliance workflows, including systematic tenant data purging across all analytical storage tiers
• Develops internal platform analytics modules to track, aggregate, and report infrastructure consumption and operational expenditures across cloud vendor ecosystems
• Establishes proactive telemetry and alerting, drives resolution for system incidents, conducts thorough root-cause investigations, and deploys long-term technical remediation
• Process
• Follows SDLC processes, including adopting agile-based processes, peer code-reviews, and technical preparations required for scheduled releases and demos.
• Partners with product, analytics and data science team to drive requirements that take into account all parties’ needs
• Establishes monitoring, responds to alerts and resolves issues within data pipelines
• Uses and helps shape AI-assisted development practices and tooling for the team.
• Impact
• Executes intricate, multi-faceted capabilities spanning microservices, automated workflows, and analytical storage infrastructure with high autonomy while providing technical leadership across mid-scale initiatives
• Assumes direct accountability for the reliability, security architecture, and long-term viability of deployed systems while systematically uncovering technical remediation opportunities
• Pinpoints architectural risks across peer technical deliverables and formulates pragmatic, alternative implementation strategies
• Streamlines operational processes, resolves critical system defects, performs advanced codebase refactoring, and exhibits expert troubleshooting capabilities across application code, cloud infrastructure, and analytical queries
• Authors comprehensive technical documentation, operational runbooks, and detailed data dictionaries to support platform capabilities
• Drives system architecture discussions and fulfills expanded peer code review obligations across the engineering organization
• Spearheads onboarding initiatives and provides technical coaching and mentorship to junior staff members

• Demonstrated background of at least six years architecting enterprise software solutions and big data platforms in operational environments.
• Required: Bachelor’s degree in Computer Science or related field, or equivalent years’ experience
• Advanced proficiency in Python engineering, spanning distributed microservices, internal modules, RESTful interface design, unit testing frameworks, and GitHub Actions release pipelines rather than ad-hoc scripting.
• Expert SQL query optimization, data modeling techniques, and extensive background delivering cloud warehouse architectures using Snowflake.
• Proven mastery deploying and orchestrating data processing flows in live production through Apache Airflow.
• Hands-on expertise utilizing Amazon Web Services ecosystems, including AWS Lambda, S3 storage, Glue jobs, IAM policies, Key Management/Secrets Manager, and EventBridge integration.
• Deep comprehension of multi-tenant security architecture-incorporating row-level access policies, fine-grained access governance, strict tenant isolation, and compliant handling of restricted financial assets across international cloud regions.

• Track record of effective cross-functional partnership in product-driven organizations alongside engineering peers and product managers. Preferred:

• Snowflake advanced features: row access policies, secure views, dynamic tables, stored procedures, Cortex AI / Cortex Analyst, semantic views.
• Experience building LLM-powered or text-to-SQL features, or other GenAI applications in production.
• Spark (AWS Glue or Databricks).
• Fivetran or an equivalent ELT tool; Looker or an equivalent BI platform, including embedded analytics.
• Infrastructure as code and GitHub Actions.
• Experience with ML-assisted data matching or entity resolution.
• Financial, expense or travel industry experience.

Why Emburse? Finance is changing-and at Emburse, we’re leading the way. Our AI-powered solutions help organizations eliminate inefficiencies, gain real-time visibility, and optimize spend-so they can focus on what’s next, not what’s slowing them down.

• A Company with Momentum - We serve 12M+ users across 120 countries, helping businesses modernize their finance operations.

• A Team That Innovates - Work alongside some of the brightest minds in finance, tech, and AI to solve real- world challenges.

• A Culture That Empowers - Competitive pay, flexible work, and an inclusive, collaborative environment that supports your success.

• A Career That Matters - Your work here drives efficiency, innovation, and smarter financial decision-making for businesses everywhere. Shape your future & find what’s next at Emburse.