Data engineer

IntellectoKids; Remote; GBP 50,000 - 80,000; Full time

Job summary

A leading educational app developer in the UK is seeking a skilled Data Engineer focused on enhancing data capabilities, reliability, and infrastructure. The position involves designing and maintaining robust data pipelines, integrating various data sources, and ensuring data quality. Ideal candidates will have 4+ years of experience, proficiency in Airflow and PostgreSQL, and be fluent in Russian and English. This full-time remote role offers autonomy and growth opportunities in the expanding EdTech sector.

Benefits

High degree of autonomy

Growth opportunities

Dynamic team environment

Qualifications

• 4+ years of experience as a Data Engineer, including 1+ year at a Senior level.
• Deep knowledge of Airflow for pipeline monitoring.
• Strong command of PostgreSQL and SQL.

Responsibilities

• Drive data engineering excellence and analyze existing practices.
• Design, develop, and maintain data pipelines using AWS.
• Integrate various data sources including mobile apps.

Skills

Data engineering excellence

DAGs and custom operators in Airflow

PostgreSQL expertise

SQL knowledge

Python programming

ETL/ELT pipeline development

Business fluent in Russian and English

Tools

AWS stack (S3, Glue, Redshift, Lambda, CloudWatch)

CI/CD with GitHub

Job description

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.

Data Engineer

We're looking for a skilled Data Engineer t o drive the evolution of our data capabilities with the focus on accessibility and reliability, design and maintain robust data infrastructure and pipelines.

Working format:

full-time, remote.

Schedule:

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

Responsibilities:

Drive Data engineering excellence. Continuously analyze existing data practices and propose improvements.

Participate in architectural decisions and technology selection .

Design, develop, and maintain data pipelines using our AWS based tech stack (S3, Redshift, Glue, Athena, Apache Airflow)..

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

Set transparent expectation levels and continuously improve data quality, consistency, and availability .

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

Evolve observability practices: pipeline monitoring , alerting , and logging .

Optimize datastores storage and performance , share query/processing best practices with the users.

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.

Ability and willingness 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:

Knowledge and relevant experience with Kotlin and Golang (if not the case - should be learned in a fast pace).

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

[e-mail]

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