Cloud Data Engineer — Azure Data Lake & Pipelines Expert

Sii Poland

Gliwice

On-site

PLN 180,000 - 280,000

Full time

8 hours ago

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Benefits offered by this job

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Job summary

Sii Poland is seeking a data processing expert to design, build, and optimize scalable data platforms in a Data Lake/Data Platform architecture. You will develop ETL/ELT pipelines in Azure Databricks and model data for analytics in collaboration with BI and Data Science teams.

The role requires 4+ years of experience with SQL, Python, and Spark, plus hands-on Azure data services (Databricks, Data Factory, Synapse, Fabric).

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 fluency required.
Location: Poland-based.

Responsibilities

Designing, building, and developing scalable data processing platforms in Data Lake / Data Platform architecture.
Creating and maintaining ETL/ELT pipelines for data integration in Azure Databricks.
Data modeling and preparing data structures for analytical and business needs.
Implementing batch and near real-time data processing solutions.
Monitoring and optimizing 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 technology solutions.
Creating and maintaining technical documentation for developed solutions.
Supporting and mentoring less experienced team members.