Job description
We’re looking for a Data Engineer to join our Data Engineering team. We build the data platform that powers decision-making across the entire company — from product insights to customer analytics.
If you enjoy building scalable pipelines, working with PySpark, AWS, and Databricks, and want to grow your expertise in a collaborative team, we’d love to hear from you.
What You’ll Actually Do Here:
You’ll be part of a team that builds and operates the data platform behind many of the company’s key functions, supporting a variety of teams with diverse use cases, from analytics to internal tools and customer-facing features. To support that range effectively, we focus on standardization, industry-standard tooling, and best practices that make our solutions scalable, reliable, and easy to maintain.
Here’s what you’ll spend most of your time on:
- Build and maintain reliable data pipelines (batch and streaming) using PySpark, SQL, and AWS
- Help develop and scale our company-wide Data Lake on AWS and Databricks (operating at petabyte scale)
- Work with data from diverse sources: APIs, file systems, databases, event streams
- Contribute to internal tooling (e.g., schema registries) to improve workflows
- Write clean, tested code and participate in code reviews
- Collaborate closely with other engineers, analysts, and product teams to deliver data solutions
- Learn and experiment with new tools and best practices in modern data engineering
What You’ll Bring to Us
Must-Have Skills
- Python – clean code, testing, and ability to read existing codebases
- Apache Spark – development and basic performance tuning
- SQL – good understanding and hands-on experience
- Git – solid version control habits
- Strong English – comfortable working and communicating in an international team
- Distributed systems mindset – solid understanding of fault tolerance, data partitioning, shuffling, and parallel processing
Nice-to-Have Skills
- Delta Lake, Databricks
- Apache Airflow or similar orchestration tools
- Amazon S3, AWS experience overall
- Streaming & messaging technologies – Kafka, Kinesis, RabbitMQ
- Python libraries for RESTful APIs
- Data modeling
- PostgreSQL, ElasticSearch
- Familiarity with JVM languages (e.g., Java, Scala)
Beyond the Tech
Besides strong technical skills and clear communication, we value the ability to explain technical concepts clearly and contribute with your own ideas. We also appreciate a broad understanding of the modern data landscape and awareness of industry best practices.
Tech Stack Snapshot
- Languages & Tools: Python with PySpark, SQL, Git
- Data & Storage: AWS S3, Databricks, Delta Lake, PostgreSQL, ElasticSearch
- Streaming: Kafka, Kinesis, RabbitMQ
- Workflow & Orchestration: Apache Airflow
- Infrastructure: AWS (core services), Docker
What We Offer
- International, fast paced and rapidly growing environment
- Opportunity for professional growth and development
- Possibility to learn new and cutting edge technologies, in an environment that encourages new ideas
- Work in an international environment in our new modern offices in Karlín
- Unlimited PTO
- Multisport card
- Home office working
- There’s more as well! Speak with us to find out all the details!
At Emplifi, we build tools that help brands better understand and serve their customers. Our Data Engineering team makes that possible by ensuring clean, reliable, and timely data for all teams across the company.
We value collaboration, technical quality, and continuous learning, and we’re excited to meet people who share those values.
At Emplifi, we are committed to creating a workplace where everyone is valued, respected, and empowered to bring their whole selves to work. We welcome applications from individuals of all ages, races, religions, genders, sexual orientations, gender identities, and LGBTQ+ communities.
Emplifi offers a safe, inclusive, and supportive environment where every employee has the opportunity to thrive and is encouraged to be who they are.
