Senior Data Engineer

Key details

• Own the full lifecycle of business critical data pipelines: define SLAs, implement performance measurement, monitoring, alerting, and anomaly detection, and lead incident response and root-cause analysis
• Define scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization
• Design, build, and maintain robust ETL/ELT data pipelines that process terabyte- to petabyte-scale data across Snowflake, BigQuery, and other platforms
• Design, build and maintain streaming and batch systems that power real-time and analytical workloads, and lead simplification of legacy ingestion paths
• Drive warehouse standardization and technical-debt reduction as we consolidate toward one warehouse
• Drive enterprise data integrity, validation, documentation, and governance practices — and the tooling that makes them the default rather than the exception
• Apply AI to accelerate the team's own work (e.g., building reusable Claude skills for pipeline migrations and upgrades) and share those patterns with individual teams
• Set and evolve engineering standards, patterns, and best practices for data modeling, pipeline design, testing, and observability
• Write and review production Java and Python code across our evolving platform stack — from data ingestion and event processing to REST services and internal tooling
• Architect and scale streaming and batch processing systems (Flink, Spark, Kafka) that power real-time and analytical workloads
• Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days)
• Design, operate, and continuously improve cloud infrastructure on AWS, applying strong judgment on performance, scalability, and cost
• Lead large size initiatives end to end: technical specs, design reviews, project planning, and delivery across teams
• Set and uphold code and data quality through leadership in design and code review, and act as a technical mentor to engineers on the team and in the domains you enable
• Translate ambiguous, cross-organizational data problems into clear, standardized solutions, and communicate effectively with both technical and business stakeholders
• Work with independence and a mandate to leave things better than you found them, in a fast-paced, globally distributed environment
• Partner with Product, Design, Analytics, and Data Science leaders to shape specifications, challenge requirements constructively, and deliver high-impact solutions
• Company mission
• Information not specified