[Hiring] Principal Data Engineer @Boldin

Role Description

The Principal Data Engineer is a senior technical authority responsible for defining Boldin’s data architecture, setting long-term technical strategy, and tackling our most complex data engineering challenges. This role shapes company-wide data standards, and partners with executive and cross-functional leaders to ensure our data platform scales with the business.

• Define and evolve long-term data architecture and vision
• Design resilient and scalable data platform and pipelines
• Set standards for data modeling, reliability, observability, and governance
• Lead complex, high-risk technical initiatives and migrations
• Influence tool selection, and technology adoption across the data stack
• Elevate engineering excellence
• Partner with leadership to align data strategy and business goals
• Enable analytics, ML, and product use cases

KPIS + Targets:

• Uptime: Consistently meets SLA for business-critical pipelines
• Freshness: All Tier 1 datasets delivered within SLA
• Delivery predictability: Majority of sprint commitments completed as planned
• Cost optimization: Year-over-year efficiency improvement as data scales
• Documentation: Full coverage for all production-grade assets

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
• 10+ years of experience in data engineering or related disciplines
• Proficient in SQL, Python, or related languages
• Cloud Platforms (AWS, GCP)
• Strong experience with data warehouse, data lakes, and distributed systems
• Strong experience with modern data stack (e.g., Athena, BigQuery, Glue, Spark, Dataproc, Kafka, Flink, dbt, Kestra, Fivetran or equivalent)
• Proven ability to build and maintain production-grade ELT/ETL pipelines
• Experience with workflow orchestration (e.g., Airflow, Dagster, Prefect, Cloud Composer or equivalent)
• Experience implementing data quality and observability frameworks
• Performance and cost optimization in cloud warehouses
• Experience supporting product analytics and experimentation
• Ability to translate business requirements into scalable data models
• Strong ownership and accountability for SLAs

Requirements

• Experience working with Kubernetes
• Experience structuring data for ML or AI use cases
• Familiarity with Amplitude or product event pipelines
• Experience in a high-growth SaaS or fintech environment
• Influencing technical direction without direct managerial authority

Benefits

• Salary Range: $180,000 - $220,000/annual DOE
• Inclusive hiring process
• Encouragement for applications from individuals of all backgrounds
• Commitment to providing reasonable accommodations for applicants with differing abilities
• Fostering an environment where everyone can bring their authentic selves to work