Data Analytics Engineer
Bengaluru (Hybrid)
One’s mission is simple - to help customers achieve financial progress. We’re doing this by creating simple solutions to help our customers save, spend, borrow, and grow their money – all in one place.
The U.S. consumer today deserves better. Millions of Americans today can’t access credit, build savings or wealth, and are left to manage their financial lives through multiple disconnected apps. Almost a quarter of U.S. adults are unbanked or underbanked and roughly 80% of fintech users rely on multiple accounts to manage their finances.
What makes us unique? We are backed by a preeminent fintech investor (Ribbit) and the world’s largest retailer (Walmart), maintain the speed and independence of a startup, and employ a strong (and growing) collection of world-class talent.
There’s never been a better moment to build a business that helps people achieve financial progress. Come build with us!
The Role:
As an Analytics Engineer at ONE, you play a crucial role in transforming vast amounts of data into actionable insights, enabling faster and informed business decisions. You'll be responsible for designing and building performant analytical data models, collaborating with stakeholders, influencing infrastructural designs, and contributing to the development of insightful data dashboards. Working closely with data engineering and product analytics teams, you'll be at the forefront of driving our analytical vision.
The role is responsible for :
Own and lead analytics engineering of key areas, influence key decision makings in data infra and business
Design and build scalable analytical data pipelines and models
Collaborate with product and business stakeholders to craft insightful metrics, and create dashboards that drive business strategy
Triage incidents, debug data issues to ensure data fidelity
Test and monitor data marts for accuracy and freshness
Maintain existing data models to iterate logics based on product/business updates
You Bring:
7+ years of analytical experience, including 2+ year in data pipelining and modeling
Preferred data stack: dbt / Looker
Strong proficiency in SQL
Experience building analytical models
An ownership mentality: decisive, collaborative, and adept at prioritization
Proven ability to collaborate across functions to solve complex data problems
Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences
Intellectual curiosity and a focus on understanding the 'why'
In order to thoughtfully scale the company and avoid downstream inequities, we’ve adopted a flat titling structure at One. Though we may occasionally post a role externally with a prefix such as “Senior” to reflect the external level of the position, we do not use prefixes in titles like that internally unless in a position which manages a team. Internal titles typically include your specific functional responsibility, such as engineering, product management or sales, and often include additional descriptors to ensure clarity of role and placement within our organization (i.e. “Engineer, Platform”, “Sales, Business Development” or “Manager, Talent”). Employees are paid commensurate with their experience and the internal level within One.
Inclusion & BelongingTo build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at talent@one.app.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Data Analytics Data pipelines dbt Engineering FinTech Looker Pipelines SQL
Perks/benefits: Startup environment
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