Data Operations Analyst

GEEIQ

Data Operations Analyst managing operational data access and quality at a marketing analytics startup. Collaborating within a tight-knit team to ensure reliable data for product and client services.

Posted 7/13/2026full-timeLondon • 🇬🇧 United KingdomJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data access management, validation, and quality control, with a strong focus on using AI tools to enhance data operations. Proficient in SQL and NoSQL databases, ensuring data accuracy and effective communication between technical and business teams.

Highest-signal resume keywords

Data Fluency (SQL & NoSQL)AI-First WorkingTechnical LiteracyRigour and Attention to DetailClear Communicator

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLNoSQLMongoDBElasticsearchPythonData ValidationData Quality ControlDatabase QueryingData Import ManagementData Documentation

Soft Skills

Operations MindsetProblem SolvingAttention to DetailBias for ActionCross-Functional Collaboration

Tools & Technologies

AI Tools (Claude, Cursor, Copilot)LinearNotion

Industry Keywords

Data OperationsBusiness IntelligenceRevenue OperationsSaaSAnalytics Operations

Tech Stack

Tools & technologies

ElasticSearchMongoDBNoSQLPythonSQL

About the role

Key responsibilities & impact

Own data access across the product lifecycle: Be the team's first port of call for data requests, pull, shape and deliver data in the format product, CS and sales need.
Validate and quality-check: Sanity-check, validate and QC data across the platform so the team can trust every number. Spot anomalies, chase them down, and keep our data honest.
Manage imports and ingestion ops: Run routine data imports and ingestion tasks, making sure data lands cleanly, completely and on time.
Work AI-first: Use AI tools (Claude, Cursor, Copilot and similar) to rapidly translate business logic or SQL into complex database queries (including NoSQL / Elastic / Mongo), accelerating repetitive work, and continually improve how the team gets and checks data.
Document and share knowledge: Document data sources, queries and processes so knowledge never sits with just one person. You make the team less dependent on any single individual, including yourself.
Own the long tail: Take ownership of the steady stream of ad hoc requests that keeps the wider team moving.
Partner cross-functionally: Work closely with data engineers and product team, translating between technical data and real business needs.

Requirements

What you’ll need

An operations and service mindset: You take genuine pride in being the reliable go-to who keeps data flowing and accurate. You enjoy solving a team's everyday data needs and you are not looking to use this role as a stepping stone into a pure engineering job.
Data Fluency (SQL & NoSQL): You write and debug SQL confidently, but you are also comfortable navigating non-relational/document databases (like MongoDB and Elasticsearch). You don't need to have raw NoSQL syntax memorized, but you should know how to read nested JSON structures.
AI-first working: You already lean heavily on AI tools to work faster and better, and you are always finding new ways to use them.
Technical literacy: You can read code and data models (including how relational data maps to NoSQL/JSON structures), understand how different systems fit together, and pick up light Python.
Rigour and attention to detail: You are meticulous about data accuracy and quality, and you notice when a number looks off.
Bias for action: You are comfortable in the ambiguity of a Series A startup and happy to roll up your sleeves and get things done.
Clear communicator: You can translate between technical data and business stakeholders without friction.
AI-first working: You already lean heavily on AI tools to work faster and better. Crucially, you possess the critical thinking to audit and validate AI-generated outputs, ensuring code/queries are safe and optimised before running them.
Experience: Around 2–4 years in a data operations, data analyst, BI, revenue/business operations or similar hands-on data role.
Bonus Points
Experience in a data operations, analytics operations or revenue operations function.
Familiarity with the modern data stack and BI tooling.
Background in marketing-related SaaS, virtual environments or gaming.
Familiarity with tools such as Linear and Notion.

Benefits

Comp & perks

Join a business at the forefront of the next big shift in marketing.
Be part of a fast-growing startup with a collaborative, innovative and supportive team.
Be genuinely indispensable, this role unlocks something the whole company depends on, so your impact is visible from day one.
A real, non-engineering growth path: grow into owning our data-quality function, take on ROI and attribution research as the team scales.
25 days holiday as standard, plus a bonus GEEIQ Day to use whenever you choose.
We offer Heka, a monthly wellness allowance you can spend across a wide range of fitness and wellbeing providers, plus a Cycle to Work scheme.
We have a thriving company culture with regular socials, team offsites, and events - quizzes, sports days, Hackathons, Bake Offs, and more. Our eNPS is 52, nearly double the industry average, and it shows, the team genuinely loves working here and learning from each other.
You pick your start time, we just ask that everyone's available during core hours of 10am–5pm.