Data Engineer – Build Scalable Data Lakehouse (Mid/Senior)

About the role

SmartCat is looking for a talented Data Engineer to design, build, and optimise a modern data lakehouse using Spark and Databricks. You will work closely with data scientists and analysts to deliver robust pipelines that support analytics and machine learning workloads.

Key responsibilities

• Design, develop and maintain scalable data pipelines with Apache Spark.
• Implement and optimise lakehouse architectures on platforms such as Databricks, Snowflake or Microsoft Fabric.
• Model data, ensure data quality, consistency and accessibility.
• Collaborate with cross‑functional teams to understand requirements and deliver solutions.
• Monitor pipeline performance, troubleshoot issues and continuously improve engineering practices.
• Provide technical guidance and mentorship to junior engineers (senior level).

Required profile

• Proven experience with Python or Scala/Java and advanced SQL.
• Hands‑on expertise with Apache Spark and at least one lakehouse platform (Databricks, Snowflake, Microsoft Fabric).
• Strong understanding of data lakehouse concepts, distributed systems and data modelling.
• Experience building cloud‑native data solutions on AWS, Azure or GCP.
• Self‑motivated learner who values work‑life balance and teamwork.

Required skills

• Python
• Scala or Java
• SQL
• Apache Spark
• Databricks
• Snowflake
• Microsoft Fabric
• Data lakehouse architecture
• Distributed systems fundamentals
• Data modelling & warehousing
• AWS, Azure or GCP

What we offer

• Transparent career path with clearly defined pay grades (L1‑L10).
• Loyalty coefficient: 10% net compensation after 3 years, 20% after 5 years.
• Knowledge budget for continuous learning.
• Flexible working hours and remote work options.
• Full visibility into salary bands, strategy and financial reports.