Pracuj.pl
None
Senior
Azure Databricks Engineer
OPTIVEUM SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ
⚲ Kraków
135–160 zł netto (+ VAT) / godz.
Wymagania
- Azure Databricks
- Delta Lake
- Python
- PySpark
- Spark
- SQL
- T-SQL
- Unix
- Hive
- Kafka
- Flink
- HBase
Opis stanowiska
Nasze wymagania:
Bachelor's degree or higher in Computer Science, Engineering or Science
8–10 years of experience, including 5+ years with Azure cloud-native services
Strong hands-on experience with Azure Databricks, Delta Lake, Python / PySpark and Spark
Knowledge of Lakehouse, Data Mesh, Data Virtualisation, dimensional modelling and data aggregation techniques
Experience building distributed data platforms (e.g. Spark, Kafka, Flink, HBase) at large scale
Hadoop-based implementations, SQL / T-SQL, Unix and Hive
Azure Data Factory, ADLS Gen2 and Azure SQL Database
Good understanding of RDBMS, Data Lake, Data Warehouse, Lakehouse and Medallion Architecture
At least one workflow orchestration tool (Apache Airflow, Luigi, Oozie, AWS Glue or similar)
Knowledge of Microsoft Fabric and basic understanding of data quality dimensions
Fluent English
Polish or EU citizenship, or a permanent residence / work permit valid for at least 12 months
O projekcie:
We are currently looking for an Azure Databricks Engineer to join the team of one of the world's leading global investment banks. The project is delivered together with a large international IT services company. For this role, Optiveum is the recruitment and contracting party, which means you will sign the cooperation agreement directly with us.
You will design and build big data solutions in Azure Databricks for batch and real-time analytics, working with Delta Lake, PySpark, Kafka streaming and the Lakehouse / Medallion architecture.
Key Details:
Rate: 135–160 PLN/h (B2B), depending on experience
Work Model: Hybrid, 3 days per week from the client's office (non-negotiable), full-time
Location: Kraków (candidates must live in or near Kraków)
Zakres obowiązków:
Design and implement big data solutions in Azure Databricks for batch and real-time analytics use cases
Build Spark pipelines that populate downstream data marts for BI and generate feeds for Data Science
Integrate real-time services that process business events from Kafka and persist them in ADLS Gen2 using Databricks
Develop near real-time stream processing to derive features for ML model inference
Optimise Databricks performance (liquid clustering, vacuum, Z-ordering etc.)
Work with DevOps teams to drive operationally excellent infrastructure
Bachelor's degree or higher in Computer Science, Engineering or Science
8–10 years of experience, including 5+ years with Azure cloud-native services
Strong hands-on experience with Azure Databricks, Delta Lake, Python / PySpark and Spark
Knowledge of Lakehouse, Data Mesh, Data Virtualisation, dimensional modelling and data aggregation techniques
Experience building distributed data platforms (e.g. Spark, Kafka, Flink, HBase) at large scale
Hadoop-based implementations, SQL / T-SQL, Unix and Hive
Azure Data Factory, ADLS Gen2 and Azure SQL Database
Good understanding of RDBMS, Data Lake, Data Warehouse, Lakehouse and Medallion Architecture
At least one workflow orchestration tool (Apache Airflow, Luigi, Oozie, AWS Glue or similar)
Knowledge of Microsoft Fabric and basic understanding of data quality dimensions
Fluent English
Polish or EU citizenship, or a permanent residence / work permit valid for at least 12 months
O projekcie:
We are currently looking for an Azure Databricks Engineer to join the team of one of the world's leading global investment banks. The project is delivered together with a large international IT services company. For this role, Optiveum is the recruitment and contracting party, which means you will sign the cooperation agreement directly with us.
You will design and build big data solutions in Azure Databricks for batch and real-time analytics, working with Delta Lake, PySpark, Kafka streaming and the Lakehouse / Medallion architecture.
Key Details:
Rate: 135–160 PLN/h (B2B), depending on experience
Work Model: Hybrid, 3 days per week from the client's office (non-negotiable), full-time
Location: Kraków (candidates must live in or near Kraków)
Zakres obowiązków:
Design and implement big data solutions in Azure Databricks for batch and real-time analytics use cases
Build Spark pipelines that populate downstream data marts for BI and generate feeds for Data Science
Integrate real-time services that process business events from Kafka and persist them in ADLS Gen2 using Databricks
Develop near real-time stream processing to derive features for ML model inference
Optimise Databricks performance (liquid clustering, vacuum, Z-ordering etc.)
Work with DevOps teams to drive operationally excellent infrastructure
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