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.

— Automate CI/CD processes for data pipelines.

— 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.

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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.