Fora Financial - Staff Data Engineer
Requirements
• Deep data engineering judgment. You have designed, built, and operated production platforms, not just individual pipelines. • Deep data engineering judgment. • Hands-on depth. You seamlessly move from architecture discussions to Python, SQL, deployment scripts, and production debugging. • Hands-on depth. • Strong ingestion fundamentals. APIs, CDC, backfills, idempotency, schema drift, and failure recovery. • Strong ingestion fundamentals. • Snowflake fluency. Warehouse design, RBAC, performance tuning, and cost controls. • Snowflake fluency. • Data quality discipline. You know which checks matter and make quality visible before users find issues. • Data quality discipline. • Independent ownership & communication. You can sequence ambiguous work, write useful design docs, align technical decisions with business outcomes, and carry problems to resolution. • Independent ownership & communication. • AI-native leverage. You actively use LLMs and agents to accelerate engineering work without outsourcing judgment. • AI-native leverage. • Lending, fintech, or financial-services data experience. • CDC, Debezium, Fivetran, Airbyte, Azure Data Factory, dbt Cloud, Dagster, Airflow, Prefect, or equivalent tooling. • Snowflake performance tuning, RBAC, data sharing, warehouse cost optimization, or Iceberg. • Data observability with Monte Carlo, Elementary, dbt tests, custom monitors, or similar. • Data contracts, source SLAs, or schema-change processes with Engineering teams. • AI-native analytics, semantic layers, MCP servers, agent QA, or governed context retrieval. • Lightweight internal tools, scripts, or agents that reduce repetitive platform work.
Responsibilities
• Architecture & Strategy • Data platform architecture: ingestion patterns, warehouse design, environment strategy, orchestration, access governance, and reliability standards. • Data platform architecture: • Freshness strategy: deciding which data needs real-time, near-real-time, daily, or ad hoc refreshes — and designing accordingly. • Freshness strategy: • Streaming vs. batch decisions: making pragmatic tradeoffs across business value, cost, complexity, failure modes, and operational burden. • Streaming vs. batch decisions: • Execution & Reliability • Source ingestion: batch, incremental, API-based, file-based, CDC, and streaming patterns where they make sense. • Source ingestion: • Pipeline reliability: dependencies, retries, alerts, backfills, incident response, runbooks, monitoring, and support expectations. • Pipeline reliability: • New source onboarding: requirements → source profiling → ingestion design → QA → documentation → support ownership. • New source onboarding: • Legacy migration: helping retire brittle reporting paths such as Azure Data Factory, SQL backup workflows, TRS Daily, and other duplicate pipelines. • Legacy migration: • Governance & Quality • Snowflake platform operations: roles, permissions, service accounts, connector ownership, environment separation, performance, cost, and governance. • Snowflake platform operations: • Data contracts: schema-change handling, new-field availability, upstream SLAs, source defects, and escalation paths. • Data contracts: • Data quality and observability: freshness, volume movement, nulls, duplicates, reconciliation, anomaly detection, and critical business-rule checks. • Data quality and observability: • AI-enabled leverage: using AI and automation to improve debugging, documentation, pipeline scaffolding, testing, monitoring, and operational workflows. • AI-enabled leverage:
Benefits
• Base salary: $175,000–$200,000 • $175,000–$200,000 • Fully remote within the US; Eastern or Central time zones preferred. • Reports to the VP of Data & AI. • Final compensation is based on scope of past ownership, technical judgment, and ability to set direction independently. • 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. • Fora Financial is a technology-enabled provider of flexible financing to small and medium-sized businesses. Since 2008, we have supported more than 55,000 merchants nationwide with over $4 billion in capital for operating expenses, cash-flow management, and growth. • Our proprietary technology helps deliver capital through a streamlined process that can be completed in as little as 24 hours, compared with the weeks or months often required for a traditional bank loan. Fora has grown from two founders in a small Manhattan workspace to a company of nearly 200 employees with a collaborative, partner-centric culture. • Equal Opportunity Statement
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