Senior Analytics Engineer

Rocket Money; Ashington; Presencial; GBP 75.000 - 110.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health, Dental & Vision Plans

Unlimited PTO

Life Insurance

Disability Insurance

Parental Leave

401k Matching

Employee Stock Purchase Program

Learning & Development

Tuition Reimbursement

Descripción de la vacante

Rocket Money is seeking a Senior Analytics Engineer to shape and scale our analytics architecture. You will design dimensional models, surface self-serve analytics for data analysts and stakeholders, and partner with data engineering and product teams to maximize data value for the business.

You will learn the intricacies of our source data, ensure data quality, and drive long-term usability and governance of analytics assets in a fast-paced environment.

Formación

• 5+ years of experience in analytics engineering, data engineering, or related roles.
• Production dbt experience with modeling, testing, macros, and maintenance of growing projects.
• Experience with BI tools (Looker preferred) and data governance concepts.
• Strong cross-functional communication and ability to influence stakeholders.

Responsabilidades

• Design and build dimensional models that scale using dbt + BigQuery.
• Translate business questions into dimensions, facts, and grain decisions.
• Define data quality checks and monitoring; own alerting and triage for data issues.
• Lead root-cause investigations on data discrepancies across the pipeline.
• Partner with Data Engineering, product engineering, and BI teams on upstream contracts and instrumentation quality.
• Support technical definitions of core business measurements and ensure stakeholder alignment.
• Guide models to enable self-service analysis for stakeholders.

Conocimientos

Dimensional modelling

Data modeling

Stakeholder communication

Problem decomposition

Cross-functional collaboration

Agile/sprint process

Data quality design

Root cause analysis

Architecture design

Self-service analytics

Herramientas

dbt Cloud

Looker

BigQuery

Amplitude

DeepNote

Descripción del empleo

• The Analytics Engineering team’s mission is to make data consistent, trustworthy, and easy to use
• We build the dimensional models that power business decisions, and we own the integrity of the data those decisions rest on
• We work in a semi-embedded structure: Analytics Engineers sit close to the Data Analyst teams they support while remaining part of a central Analytics Engineering practice
• Day to day, that means translating business questions into technical requirements, modeling ingested source data into shapes the business can actually use, and partnering with engineering teams on the upstream data we depend on
• We’re looking for a Senior Analytics Engineer to help shape that architecture as it grows
• You’ll build and iterate on our star schema, surfacing models that Data Analysts and stakeholders across the business can self-serve against with confidence
• Done well, this work raises the data literacy of the entire company — and we take that seriously
• Be a trusted builder, architect, and consultant on the analytics data we surface to our stakeholders
• You’ll learn the intricacies of our source data, how we transform it, how we monitor for integrity, and continue to move the needle on the partnership needed to maximize value for the business
• Design and build dimensional models that scale (we use dbt + BigQuery):
• Translate ambiguous business questions into dimensions, facts, and grain decisions that hold up as the business changes
• Make tradeoffs between normalization, performance, and usability, and document the reasoning behind them
• Reduce technical debt in the dbt project: model layering, naming and testing standards, macro reuse, and incremental strategy
• Own data quality and monitoring for the models you build:
• Define what “correct” means for each model and instrument data quality checks to monitor it
• Build and improve the alerting and triage process so data issues are caught proactively
• Lead root-cause investigations on data discrepancies across the pipeline, from source event or system of record through to the analytics layer
• Partner with Data Engineering and product engineering teams on upstream contracts and instrumentation quality
• Be the connective tissue between source data and business definitions:
• Support technical definition of core business measurement and drive alignment when stakeholders disagree
• Partner with Data Analysts and BI to ensure models enable stakeholder self-service analysis
• Translate business needs into technical requirements and prioritize work against them
• Raise the bar on the team through code review, design review, and documentation

Benefits

• Health, Dental & Vision Plans
• Unlimited PTO
• Life Insurance
• Long/Short Term Disability
• Parental Leave
• 401k Matching
• Team Member Stock Purchasing Program
• Learning & Development Opportunities
• Tuition Reimbursement

Deep data modeling expertise. You have designed dimensional models from scratch and integrated them into a cohesive analytics architecture to serve your stakeholders. You understand grain, SCD types, and fact table design tradeoffsProduction dbt experience. You understand model materialization strategies, testing, macros, and how to keep a growing project maintainable5+ years of experience in analytics engineering, data engineering, or related rolesStrong problem decomposition: you can understand the underlying problem in requests that you receive and align them with our modeling roadmap and architectureStrong cross-functional communication skills and the ability to influence stakeholder & business decisions2+ years of experience with BI tools (Looker preferred) and an understanding of how modeling choices shape what’s possible in the analytics layerYou treat data quality as a design problem, not a cleanup task. You have built testing and monitoring into pipelines, defined SLAs or expectations with data owners, and managed the on-call/triage side of keeping data trustworthyYou judge your work by its usability to your stakeholders over the long-term, not just by speed of delivery, underlying architecture elegance, or immediate use caseYou can handle complex modeling scenarios, such as conforming dimensions across business use cases, modeling many-to-many relationships, handling late-arriving and restated data, and keeping models usable as the source systems evolveYou have experience with our stack (BigQuery, dbt Cloud, Looker, Amplitude, DeepNote)You have worked with finance or financial services data — transactions, subscriptions, revenue recognition, ledgers, or reconciliation against a system of recordYou have experience with data governance, lineage, or catalog toolingYou’re familiar with Agile process & sprint cyclesYou have experience in mobile app or product analytics