Staff Data Engineer

🕒 il y a 7 jours

🇺🇸 États-Unis – Télétravail

💵 $175 000 - $200 000 / an

⏰ Temps Plein

🔴 Expert

🚰 Ingénieur Data

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

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Fora Financial

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2008

🏗️ Construction

🏭 Fabrication

🍽️ Alimentation et boissons

Construction • Manufacturing • Food & Beverage

Fora Financial est une entreprise de financement qui fournit des solutions de capitaux rapides et flexibles aux petites et moyennes entreprises. Depuis 2008, elle propose des produits tels que des prêts aux petites entreprises, des avances sur chiffre d'affaires, des lignes de crédit, des prêts SBA, des prêts à terme et des financements d'équipement, avec des montants de financement pouvant atteindre 1,5 million de dollars et des délais d'approbation et de financement accélérés. Fora s'associe à des banques et des fournisseurs de financement tiers pour souscrire et fournir du capital de travail dans des secteurs tels que la construction, la fabrication, le commerce de détail, le médical et la restauration, en mettant l'accent sur un service axé sur les relations et l'accès au crédit pour les entreprises avec des profils de crédit variés.

Description

• Data platform architecture: ingestion patterns, warehouse design, environment strategy, orchestration, access governance, and reliability standards. • Freshness & ingestion strategy: Deciding when to use streaming versus batch based on business value, cost, and operational burden. • Cross-functional partnership: Partnering with Platform Engineering to ensure our data infrastructure integrates securely and reliably with core operational systems. • Data Integrations: requirements → source profiling → ingestion design → QA → documentation → support. • Pipeline reliability: dependencies, retries, alerts, backfills, incident response, runbooks, monitoring, and support expectations. • Legacy migration: helping retire brittle reporting paths such as Azure Data Factory, SQL backup workflows, and other duplicate pipelines. • Snowflake governance: roles, permissions, service accounts, connector ownership, environment separation, performance, cost, and governance. • Data contracts: schema-change handling, new-field availability, upstream SLAs, source defects, and escalation paths. • Data observability: freshness, volume movement, nulls, duplicates, reconciliation, anomaly detection, and critical business-rule checks. • AI-enabled leverage: using AI and automation to accelerate debugging, documentation, pipeline scaffolding, and operational workflows.

🎯 Exigences

• Deep data engineering judgment. You have designed, built, and operated production platforms, not just individual pipelines. • Hands-on depth. You move seamlessly from high-level architecture to writing production code, standing up CI/CD workflows, and debugging pipeline failures. • Strong ingestion fundamentals. APIs, CDC, backfills, idempotency, schema drift, and failure recovery. • Snowflake fluency. Warehouse design, RBAC, performance tuning, and cost controls. • Data quality discipline. You know which checks matter and make quality visible before users find issues. • Ownership & communication. You can sequence ambiguous work, write useful design docs, align technical decisions with business outcomes, and carry problems to resolution. • Cross-functional partnership. You work with stakeholders across Engineering, Analytics, and the business to understand needs, define clear requirements, and build trust. • AI leverage. You use LLMs and agents to accelerate your own work, and you build data products that agents can consume safely.

🏖️ Avantages

• Company-subsidized medical, dental, and vision plans. • 401(k) plan with company match. • Life insurance at no cost to employees. • Generous time off plan, including rollover vacation days. • Health care and dependent care flexible spending accounts. • Commuter benefits. • Remote working model. • Weekly breakfast, snacks, and Friday lunches provided onsite.