Data Engineer

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InPost Group

WebsiteLinkedInAll Job Openings

10,000+ employees

🛍️ eCommerce

🚗 Transport

eCommerce • Transport • Logistics

InPost Group is Europe's leading e-commerce enablement platform, specializing in out-of-home delivery services. Founded in 1999 by CEO Rafal Brzoska, InPost provides cost-effective and environmentally friendly delivery solutions through a robust network of Automated Parcel Machines (APMs) and courier services. The company also offers pick-up drop-off (PUDO) services, enhancing convenience and efficiency for e-commerce merchants across Europe. InPost is committed to sustainability, reducing carbon emissions significantly in its delivery processes. With operations in countries like Poland, France, Benelux, the UK, and Italy, InPost continues to expand its innovative technology solutions to drive long-term growth in the e-commerce sector.

📋 Description

• Design, build, and maintain scalable data lake solutions and processing pipelines handling large volumes of structured and semi-structured data. • Build and operate real-time data streaming pipelines using Apache Kafka and its ecosystem (Kafka Streams, Kafka Connect). • Architect and maintain ETL and ELT pipelines with a focus on data quality, idempotency, and observability. • Develop distributed data processing applications using Apache Spark (PySpark, Scala), running on Databricks. • Design and manage both SQL and NoSQL databases used in our data products. • Build data solutions on cloud infrastructure (GCP, Azure, or AWS), leveraging managed services. • Apply software engineering best practices to data pipelines: version control, automated testing, peer code review, and CI/CD using tools such as GitLab or Jenkins. • Own the operational health of the data infrastructure and ETL processes you build. • Integrate data from internal and external sources via REST and SOAP APIs. • Actively contribute to InPost's data engineering community — through code reviews, internal documentation, tech talks, and mentoring.

🎯 Requirements

• At least 3 years of experience in a Data Engineering or similar role • Hands-on experience with Apache Spark (Streaming, Spark SQL, MLlib) and Databricks (PySpark, Scala) • Practical experience with Apache Kafka — including Kafka Streams and Kafka Connect • Proficiency in Python; working knowledge of Scala or Java • Experience designing and operating SQL databases (e.g., PostgreSQL, BigQuery, Spark SQL) and NoSQL databases (e.g., MongoDB, Cassandra, or similar) • Experience building and maintaining data lake environments (Delta Lake, Parquet, or equivalent) • Familiarity with cloud platforms (GCP, Azure, or AWS) and their managed data services • Experience integrating data via REST and/or SOAP APIs • Working knowledge of CI/CD tooling (GitLab CI, Jenkins, or equivalent) and software engineering practices (testing, versioning, code review) • Experience building and running Docker containers • Willingness to share knowledge and actively contribute to engineering best practices • Professional working proficiency in both English and Polish.

🏖️ Benefits

• The option to work from the office or 100% remotely • Opportunity to work in a diverse, international and cross-functional environment, along with leading experts. • Fulfilling careers with a range of benefits and invests in providing training opportunities for their development. • Involvement in technology monitoring and choices • Your impact will be visible instantly and you will be making a difference in our users lives • We offer B2B type of cooperation