Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data engineer

IntellectoKids
London
1 week ago
Create job alert

IntellectoKids is one of the world’s largest developers of educational apps for children ages 2 to 7. Our products are among the top 15 in the preschool apps category globally.

We're looking for a skilled Data Engineer to design and maintain robust data infrastructure and pipelines, driving data accessibility and reliability across our platform.

Working format: full-time, remote.

Schedule: Monday to Friday (the working day is 8+1 hours).

Responsibilities:

Design, develop, and maintain data pipelines using Apache Airflow.

Create and support data storage systems (Data Lakes / Data Warehouses) based on AWS (S3, Redshift, Glue, Athena, etc.).

Integrate data from various sources, including mobile apps, third-party APIs, and internal services.

Ensure data quality, consistency, and availability.

Support analysts: build user-friendly data marts and contribute to schema and data model design.

Set up pipeline monitoring, alerting, and logging.

Participate in architectural decisions and technology selection.

Optimize existing data storage systems and complex SQL queries.

Your goals and KPIs during the probation period:

Design and implement a data quality monitoring system for the raw data layer.

Review and analyze current data source integrations, identifying bottlenecks and proposing improvements to enhance data reliability and performance.

Key long-term goals:

Architect and evolve the analytical data delivery pipeline into a standalone, scalable service.

What we expect from you:

4+ years of experience as a Data Engineer, including 1+ year at a Senior level.

Deep knowledge of Airflow: DAGs, custom operators, and monitoring.

Strong command of PostgreSQL databases; familiarity with the AWS stack (S3, Glue or Redshift, Lambda, CloudWatch) is a significant plus.

Excellent SQL skills and confident Python programming.

Knowledge of Kotlin and Golang, and the ability to work with unfamiliar codebases.

Experience building robust ETL/ELT pipelines.

Understanding of data warehouse (DWH) design principles and data normalization.

Ability to work under uncertainty, prioritize tasks, and propose practical solutions.

Skill in reading documentation and understanding the limitations and capabilities of technologies.

Understanding of development practices (CI/CD, DevOps) and the ability to solve infrastructure-related challenges within the Data Engineer’s scope.

Business fluent Russian and English.

Would be a plus:

Experience with tools such as Firebase Analytics, Amplitude, Adjust, AppsFlyer, or similar SDKs/platforms. Understanding of event structures, attribution, retention, LTV, and other mobile metrics. Ability to collect and aggregate user data from mobile sources for analytics.

Experience building real-time data pipelines (e.g., Kinesis, Kafka, Spark Streaming).

Hands-on CI/CD experience with GitHub.

Startup or small team experience — the ability to quickly switch between tasks, suggest lean architectural solutions, make independent decisions, and take ownership of the result.

What do we offer?

A high degree of autonomy and responsibility.

An exciting opportunity in the rapidly growing EdTech industry within a very dynamic team.

Growth opportunities as the company expands, with potential for professional development within the role and gradual transition to more complex and strategic tasks.

Contacts

167 City Road,
London, Greater London, United Kingdom, EC1V 1AW


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.

Automate Your Data Science Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

Data science roles land daily across banks, product companies, consultancies, scaleups & the public sector—often buried in ATS portals or duplicated across boards. The fix: put discovery on rails with keyword-rich alerts, RSS feeds & a reusable ChatGPT workflow that triages listings, ranks fit, & tailors your CV in minutes. This copy-paste playbook is for www.datascience-jobs.co.uk readers. It’s UK-centric, practical, & designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning Core DS, Applied/Research, Product/Decision Science, NLP/CV, Causal/Experimentation, Time Series/Forecasting, MLOps-adjacent & Analytics Engineering overlaps. Shareable Boolean searches for Google & job boards that strip out noise. Always-on alerts & RSS feeds that bring fresh UK roles to you. A ChatGPT “Data Science Job Scout” prompt that deduplicates, scores match & outputs ready-to-paste actions. A simple pipeline tracker so deadlines & follow-ups never slip.