Ripple

3 weeks ago

Staff Software Engineer, Data Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build and lead technical direction for the Caspian Data Platform on Ripple’s Data Engineering team, shaping ingestion, transformation, governance, and data quality. Define Databricks pipeline patterns and ship production flows with reference implementations. Establish data-quality and governance standards, lead complex multi-quarter initiatives, and drive AI into data engineering workflows—including agentic pipeline operations and automated transformation generation.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead the design of core platform pillars—ingestion, transformation, governance, and data quality—and build the most critical components yourself.
•Define engineering patterns and reference architectures for Databricks pipelines; ship production flows and prototype hard parts before scaling.
•Establish and enforce benchmarks for data quality and governance, including data contracts, lineage, validation frameworks, and code review.
•Lead the most complex, ambiguous initiatives spanning multiple quarters and teams from problem statement to delivered capability.
•Drive the technical direction for applying AI across data engineering, including agentic systems for pipeline operations and self-serve analytics interfaces.

Pay and Benefits

Salary: USD 212,000 - 265,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceRetirementLearning BudgetMobile PhoneParental LeaveWellness StipendPaid Leave

Key Requirements

•10+ years of data engineering experience architecting and operating data platforms at scale while staying hands-on.
•Deep mastery of Databricks (Delta Live Tables, Unity Catalog, Delta Lake, Spark) to make platform-level decisions and implement them.
•Proven ownership of ingestion, transformation, governance, and data quality across a production platform.
•Expertise in SQL and Python for complex data modeling, transformations, and platform tooling.
•Strong AWS experience operating data systems at scale, plus experience integrating AI tooling into data engineering workflows.

Experience:Data engineeringData platforms

Skills:Engineering judgmentMentorshipTechnical credibilityLeadershipProblem-solving

Languages:English

Tech Stack:DatabricksDelta Live TablesUnity CatalogDelta LakeSparkSQLPythonAWSLLMs

Company Brief

Ripple

Website

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Ripple

3 weeks ago

Staff Software Engineer, Data Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead the design of core platform pillars—ingestion, transformation, governance, and data quality—and build the most critical components yourself.
•Define engineering patterns and reference architectures for Databricks pipelines; ship production flows and prototype hard parts before scaling.
•Establish and enforce benchmarks for data quality and governance, including data contracts, lineage, validation frameworks, and code review.
•Lead the most complex, ambiguous initiatives spanning multiple quarters and teams from problem statement to delivered capability.
•Drive the technical direction for applying AI across data engineering, including agentic systems for pipeline operations and self-serve analytics interfaces.

Pay and Benefits

Salary: USD 212,000 - 265,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceRetirementLearning BudgetMobile PhoneParental LeaveWellness StipendPaid Leave

Key Requirements

•10+ years of data engineering experience architecting and operating data platforms at scale while staying hands-on.
•Deep mastery of Databricks (Delta Live Tables, Unity Catalog, Delta Lake, Spark) to make platform-level decisions and implement them.
•Proven ownership of ingestion, transformation, governance, and data quality across a production platform.
•Expertise in SQL and Python for complex data modeling, transformations, and platform tooling.
•Strong AWS experience operating data systems at scale, plus experience integrating AI tooling into data engineering workflows.

Experience:Data engineeringData platforms

Skills:Engineering judgmentMentorshipTechnical credibilityLeadershipProblem-solving

Languages:English

Tech Stack:DatabricksDelta Live TablesUnity CatalogDelta LakeSparkSQLPythonAWSLLMs

Company Brief

Ripple

Website