What You’ll Do
Data Engineering, Frameworks & AI‑Driven Automation
Design, build, and maintain scalable batch and streaming data pipelines
Develop reusable data engineering frameworks, libraries, and templates for ingestion, transformation, validation, and publishing
Establish standardized patterns for data modeling, transformations, and pipeline orchestration
Implement end-to-end data workflows from raw ingestion to curated analytical datasets
Leverage AI‑based techniques to automate and optimize data engineering workflows, such as:
Intelligent schema inference and evolution
Automated data quality checks and anomaly detection
Pipeline failure detection and self-healing mechanisms
Ensure data quality, reliability, and performance across pipelines and shared frameworks
Support downstream consumers such as analytics, reporting, and AI/ML teams
Reliability, Operations & Intelligent Automation
Define and monitor SLIs/SLOs for data pipelines, frameworks, and platform availability
Participate in incident response, on-call rotations, and post-incident reviews
Apply AI‑assisted monitoring and alerting to proactively detect performance issues, data drift, and operational anomalies
Implement security, compliance, and data governance controls across shared data assets
Drive performance tuning and cost optimization, including automated recommendations for resource utilization and workload optimization
Collaboration & Technical Leadership
Partner with analytics, application, and platform teams to understand common data needs and platform gaps
Drive adoption of standardized data frameworks, automation patterns, and best practices across teams
Contribute to data architecture decisions, platform standards, and design guidelines
Mentor junior engineers and provide technical guidance, including best practices for automating data workflows
Qualifications
Data Engineering, Frameworks & System Design
8+ years of experience building and operating data platforms or distributed data systems
Proven experience designing and building reusable data engineering frameworks, libraries, or platform components
