MacPaw is a software company that develops and distributes software for macOS and iOS. Today, we have 20 million active users across all our products, and every 5th Mac on Earth has our product installed.
At MacPaw, we believe humans and technology can reach their greatest potential together.
We gather open-minded people who support each other and aspire to change the world around us, making millions of people’s lives easier with technology.
Our flagship products include CleanMyMac, Setapp, ClearVPN, Moonlock, and more. Now, we’re stepping into an important new stage: launching a product ecosystem with a new AI Mac Assistant — Eney.
We are expanding our team and looking for a Data Engineer to help us build a scalable, reliable data architecture.
In this role, you will build reliable data pipelines, design clear domain models, and optimize our data warehouse. We value a practical, problem-solving mindset — someone who easily navigates ambiguous requirements, brings structure to complex tasks, and takes ownership of their solutions.
In this role, you will:
Build and support Airflow pipelines to ingest data from third-party sources (APIs, payment providers, ad networks) with retries, backfills, and quality checks.
Work directly with Analytics Engineers and product teams to translate ambiguous business requests into reliable data models.
Design and implement fact and dimension tables in dbt using dimensional modeling principles.
Migrate existing SQL transformations into dbt models, adding tests and documentation.
Refactor the current dbt project: improve layer structure, standardize naming conventions, and set up CI checks.
Optimize slow or costly warehouse queries and materializations.
Evaluate table formats and set up initial ingestion flows for our Data Lakehouse prototype.
Skills you’ll need to bring:
Strong proficiency in Python and advanced SQL, including complex transformations, window functions, and query optimization.
Proven experience building and orchestrating ELT/ETL pipelines using Airflow.
Solid experience with dbt for data modeling, testing, documentation, and managing project structure.
Good understanding of dimensional modeling concepts, Kimball methodology, star/snowflake schemas, and SCDs.
Practical experience working with cloud data warehouses (preferably BigQuery, Redshift, or Snowflake) and Cloud Storage.
Hands-on experience with Docker, Git workflows, and basic cloud/containerized environments.
A problem-solving mindset with the ability to handle ambiguous requirements, communicate effectively with stakeholders, and use AI/LLM tools (like Claude) to speed up delivery.
At least an Intermediate level of English and fluent Ukrainian.
As a plus:
Experience with change data capture (CDC) tools and patterns (e.g., Debezium).
Background in building and optimizing large-scale data processing jobs with PySpark.
Experience with real-time data processing using message brokers like Kafka or RabbitMQ.
Experience with stream processing frameworks (Flink, Kafka Streams).
What we offer:
We are a Ukrainian company, and we stand with Ukraine against the russian aggression We maintain workplaces for the mobilized Macpawians and provide financial support to colleagues or their families affected by the war. Here, you can also read about the MacPaw Foundation, which intends to help save the lives of Ukrainian defenders and provide relief to as many civilians as possible.
We are committed to our veterans Our Veteran Career and Empowerment Program is designed to ensure our veterans and active military personnel receive the recognition, support, and opportunities they deserve.
Hybrid work model Whether to work remotely or at the hub is entirely up to you. If you decide to mix it, our Kyiv office, which works as a coworking space, is open around the clock. The office is supplied with UPS and Starlink for an uninterrupted work process.
Your health always comes first We guarantee medical i
