5+ years of experience in data engineering, analytics engineering, or a technical data role.
Proficiency in building and maintaining ETL or ELT pipelines using modern data tools.
Experience with data warehouses, transformation frameworks, and BI tools.
Strong SQL skills and capability of building production-grade data models.
Ability to transform ambiguous business questions into clear data models and recommendations.
Experience in partnering with engineering teams on tracking and event schemas.
Strong communication skills to convey technical data insights effectively.
Familiarity with growth analytics, including attribution, funnel analysis, and SEO.
Responsibilities
Own Venn's entire data infrastructure, enhancing product, finance, risk, and operational decisions.
Build ETL and ELT pipelines for diverse data sources, ensuring effective data transformation.
Design accessible and reliable data models and analytics layers for company-wide use.
Collaborate with engineering to ensure data reliability and scalability from the outset.
Enhance data quality, documentation, and governance across the data stack.
Empower cross-team usage of AI workflows and data tools for independent analysis.
Develop dashboards and reports for essential metrics impacting various business facets.
Benefits
Competitive salary.
Latest tech and equipment provided.
Full Job Description
What You'll Be Doing
Own Venn's data infrastructure, including pipelines, models, warehouses, and reporting layers that power product, finance, risk, operations, marketing, and leadership decisions.
Build reliable ETL and ELT pipelines that ingest, transform, and structure data from our core product, banking partners, card processors, payment systems, accounting integrations, CRM, marketing tools, and internal systems.
Design clean, trusted data models and analytics layers that make business-critical data easy to access, understand, and use across the company.
Partner with engineering on event schemas, tracking requirements, and measurement architecture to ensure data is reliable, scalable, and built correctly from the start.
Improve data quality, observability, documentation, lineage, testing, and governance across the stack.
Empower teams across Venn to use AI-assisted workflows, MCPs, and trusted data tools to safely query data, run analysis, and answer business questions independently.
Build dashboards, reports, and self-serve workflows for core company metrics, including transaction volume, card spend, FX, balances, revenue, activation, retention, onboarding conversion, acquisition, and risk signals.
Support marketing, growth and sales measurement where needed, including attribution, paid media incrementally, web analytics, CRO, lifecycle analytics, SEO, and organic acquisition reporting.
Help translate complex data into clear recommendations that influence product, GTM, finance, and leadership decisions.
What You'll Need
5+ years of experience in data engineering, analytics engineering, or a highly technical data role.
Experience building and maintaining reliable ETL or ELT pipelines using modern data tooling.
Experience working with data warehouses, transformation frameworks, BI tools, and event or product analytics systems.
Strong understanding of data quality, testing, documentation, lineage, metric definition, and analytics reliability.
Strong SQL skills and experience building production-grade data models.
Ability to translate ambiguous business questions into clean data models, dashboards, and clear recommendations.
Experience partnering with engineering teams on tracking requirements, event schemas, and data infrastructure.
Comfort working cross-functionally with product, engineering, finance, operations, growth, marketing, RevOps, and leadership teams.
Experience with marketing, growth, or web analytics, including attribution, funnel analysis, paid media measurement, SEO analytics, lifecycle analytics, or CRO.
Strong communication skills, with the ability to explain technical data concepts and analytical findings in a way that drives business decisions.
Bonus Points
Experience at an early-stage or fast-growing startup.
