Azure Data Engineer: Scalable Data Lakes & Pipelines

Sii Ukraine LLC

Polska

Hybrid

PLN 180,000 - 260,000

Full time

38 hours ago

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Job summary

Sii Ukraine LLC in Poland is expanding its Data & Analytics Competency Center, seeking an experienced data engineer to design and build scalable data processing platforms, datasets for analytics, and ETL/ELT pipelines in Azure Databricks.

You will collaborate with data analysts and BI teams, model data, optimize pipelines, and document solutions; fluent English and Polish are required, with at least four years of related experience.

Qualifications

Minimum 4 years of experience in projects related to processing and integrating large volumes of data.
Strong knowledge of SQL and Python.
Experience with data processing frameworks such as Apache Spark / PySpark.
Practical experience in designing and building Data Lake and Data Warehouse solutions.
Ability to build and maintain ETL/ELT pipelines and work with data orchestration and integration tools.
Commercial experience in cloud-based Microsoft Azure data processing projects (e.g., Databricks, Azure Data Factory, Synapse, Fabric).
Knowledge of data processing concepts in a distributed environment and optimizing data pipelines.
Ability to communicate fluently in English.
Polish language fluency is required.
Required to be located in Poland.

Responsibilities

Designing, building, and developing scalable and high-performance data processing platforms in Data Lake / Data Platform architecture
Creating and maintaining ETL/ELT pipelines for data integration from various sources and processing them in the Azure Databricks environment
Data modeling and preparing data structures tailored to analytical and business needs
Implementing solutions for data processing (batch and/or near real-time)
Monitoring, optimizing, and developing existing pipelines and data processing processes
Collaborating with data analysts, BI teams, and Data Science on data preparation and sharing
Gathering business requirements and proposing optimal technological solutions
Creating and maintaining technical documentation for developed solutions
Supporting and mentoring less experienced team members, sharing knowledge and best practices

Skills

SQL

Python

Data Lake/Warehouse design

ETL/ELT pipelines

Data processing concepts

Big data

English communication

Polish language

Azure Databricks

Azure Data Factory

Synapse

Fabric

Apache Spark

PySpark

Tools