Senior Data Engineer / Databricks

We are looking for an Experienced Data Engineer with strong hands-on experience in Databricks-based data platforms. The role focuses on building, optimizing, and maintaining scalable data pipelines, data lakes, and Lakehouse solutions that enable advanced analytics and data-driven products. 

You will work on heavy data processing tasks, third-party integrations, ETL/ELT pipelines, and orchestration of data workloads in cloud environments. If you enjoy working with Databricks, Spark, large datasets, and modern cloud data stacks - and you are not constrained by a single programming language or tool - this role could be a great fit. 

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  Take ownership of data engineering features, architecture, and code quality 

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  Design, implement, and maintain Databricks-based data pipelines and workflows 

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  Build and optimize ETL/ELT processes using Apache Spark on Databricks 

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  Design and manage data lakes and Lakehouse architectures (Delta Lake) 

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  Integrate diverse data sources and ensure reliable data ingestion 

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  Automate orchestration, scheduling, and monitoring of Databricks jobs 

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  Design and implement fault-tolerant and scalable data processing workflows 

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  Ensure high data quality, consistency, and accuracy across the platform 

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  Make informed decisions about storage, compute, and performance optimization 

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  Collaborate with analytics, BI, and business stakeholders to support data-driven products 

• 7+ years of relevant experience as a Data Engineer  

• Strong hands-on experience with Databricks and Apache Spark 

• Proficiency in Python or Scala (both strongly preferred) 

• Very good knowledge of SQL, relational databases, and data warehousing concepts 

• Solid experience with ETL/ELT principles and data pipeline design 

• Hands-on experience with cloud platforms (Azure, AWS, or GCP), preferably Databricks workloads 

• Experience working with distributed systems and large-scale data processing 

• Familiarity with Unix-like operating systems 

• Experience with version control systems  

• Strong communication skills and English language proficiency 

• Databricks certifications - Professional level 

• Experience with Delta Lake, performance tuning, and cost optimization 

• Experience with streaming technologies (Kafka or similar) 

• Knowledge of workflow orchestration tools (Databricks Workflows, Airflow, etc.) 

• Experience with cloud-native and serverless data architectures 

• Familiarity with containerization and virtualization (Docker, Kubernetes) 

• Experience building data assets that directly support analytics and business decision-making