Azure Databricks Engineer

OPTIVEUM SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ; Kraków; Hybrid; PLN 186,000 - 220,000; Full time

Job summary

OPTIVEUM SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ is seeking an Azure Databricks Engineer to join a global investment bank’s team in Kraków. You will design big data solutions using Azure Databricks for batch and real-time analytics.

You will build Spark pipelines feeding BI data marts and enable data science workflows, integrating real-time events from Kafka and persisting results in ADLS Gen2. The role requires 8–10 years of experience with Azure cloud-native services, fluent English, and a

Qualifications

• Bachelor's degree or higher in Computer Science, Engineering or Science
• 8-10 years of experience, incl. 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

Responsibilities

• 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

Skills

Azure Databricks

PySpark

Spark

Kafka

Hadoop

SQL

Azure Data Factory

Azure SQL Database

Data Modeling

Airflow

Education

Bachelor's degree in CS/Engineering/Science

Tools

Delta Lake

ADLS Gen2

Azure Data Factory

Azure SQL Database

Airflow

HDFS

Job description

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.

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