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1 week ago

Staff Software Engineer, Backend (Lake Analytics Platform)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Build and evolve a large-scale Lakehouse Platform, defining the long-term roadmap across Apache Iceberg, Spark, and Snowflake. Architect platform capabilities that make analytical data secure, governed, trustworthy, and easy to use for engineering, analytics, ML, and business teams. Lead governance and access-control work, improve analytics engineering foundations (dbt, testing, CI/CD), operate and optimize the platform for performance and cost, and mentor engineers while collaborating across infrastructure and SRE.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Define and drive the long-term technical roadmap for the Lakehouse Platform, balancing scalability, reliability, governance, performance, and cost.
•Architect and implement secure, trustworthy, discoverable, and easy-to-use analytical data platform capabilities across multiple teams.
•Design and operate governed data access capabilities in Snowflake and the lakehouse platform, including RBAC, dynamic data masking, cataloging, lineage, classification, and privacy enforcement.
•Partner with Analytics Engineering to evolve data modeling, transformation pipelines, testing frameworks, documentation standards, and data quality practices for self-service analytics.
•Establish lakehouse operations best practices (schema evolution, partitioning, compaction, observability, incident response/on-call readiness) and optimize performance and cost.

Pay and Benefits

Salary: USD 204,000 - 290,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionEquityPaid Leave

Key Requirements

•8+ years of software engineering, data infrastructure, or data platform engineering experience, including 2+ years of technical leadership responsibilities.
•Proven experience architecting, building, launching, and operating large-scale OLAP systems, lakehouse platforms, or analytical data infrastructure using Apache Iceberg, Spark, Snowflake, and cloud-native storage.
•Hands-on Snowflake experience, including RBAC, dynamic data masking, and warehouse/query optimization with cost management.
•Strong data platform architecture knowledge across table formats, schema evolution, partitioning, compaction, observability, and analytical system cost optimization.
•Experience with dbt (or similar) for transformation pipelines, including data modeling, testing, documentation, and CI/CD practices.

Experience:8+ yearsFintech

Education:Bachelor's

Skills:Technical leadershipCommunicationCollaborationMentor engineersTechnical strategy

Languages:English

Tech Stack:Apache IcebergSparkSnowflakeCloud-native storagePythonSQLJVM-based languagesTerraformDbtRBACABACDynamic data maskingCI/CD

Company Brief

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Provides point-of-sale lending and buy-now-pay-later (BNPL) solutions for consumers and merchants, enabling installment payments, consumer financing, and embedded financial services through APIs and partnerships with retailers and platforms.

Industry: Lending

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2012

Website LinkedIn

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Affirm

1 week ago

Staff Software Engineer, Backend (Lake Analytics Platform)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Define and drive the long-term technical roadmap for the Lakehouse Platform, balancing scalability, reliability, governance, performance, and cost.
•Architect and implement secure, trustworthy, discoverable, and easy-to-use analytical data platform capabilities across multiple teams.
•Design and operate governed data access capabilities in Snowflake and the lakehouse platform, including RBAC, dynamic data masking, cataloging, lineage, classification, and privacy enforcement.
•Partner with Analytics Engineering to evolve data modeling, transformation pipelines, testing frameworks, documentation standards, and data quality practices for self-service analytics.
•Establish lakehouse operations best practices (schema evolution, partitioning, compaction, observability, incident response/on-call readiness) and optimize performance and cost.

Pay and Benefits

Salary: USD 204,000 - 290,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionEquityPaid Leave

Key Requirements

•8+ years of software engineering, data infrastructure, or data platform engineering experience, including 2+ years of technical leadership responsibilities.
•Proven experience architecting, building, launching, and operating large-scale OLAP systems, lakehouse platforms, or analytical data infrastructure using Apache Iceberg, Spark, Snowflake, and cloud-native storage.
•Hands-on Snowflake experience, including RBAC, dynamic data masking, and warehouse/query optimization with cost management.
•Strong data platform architecture knowledge across table formats, schema evolution, partitioning, compaction, observability, and analytical system cost optimization.
•Experience with dbt (or similar) for transformation pipelines, including data modeling, testing, documentation, and CI/CD practices.

Experience:8+ yearsFintech

Education:Bachelor's

Skills:Technical leadershipCommunicationCollaborationMentor engineersTechnical strategy

Languages:English

Tech Stack:Apache IcebergSparkSnowflakeCloud-native storagePythonSQLJVM-based languagesTerraformDbtRBACABACDynamic data maskingCI/CD

Company Brief

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Industry: Lending

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2012

Website LinkedIn