Senior Data Engineer (m/f/n)

Shimi Sp. z o.o.; Województwo mazowieckie; Remote; PLN 165,000 - 235,000; Full time

Benefits offered by this job

100% Remote

B2B via Shimi

Job summary

Shimi Sp. z o.o. in Poland seeks a Senior Data Engineer to design and deliver scalable data solutions on Azure Databricks and data lakehouse platforms for a global travel and cruise client.

You will build and optimize ETL/ELT processes, work with Python, SQL, Spark, and collaborate with cross-functional teams to enable analytics and reporting. The role requires 5+ years of Databricks experience, English level B2+, and a 100% remote, long-term engagement via B2B with Shimi.

Qualifications

• Minimum 5 years of commercial Databricks experience.
• Proficient in Spark, Python, SQL.
• Strong English, B2+ level.
• Ability to work independently with ownership.
• Experience with Azure Data Platform.

Responsibilities

• Design, develop, and maintain scalable data solutions within the Azure Data Platform ecosystem, including Azure Synapse, Databricks, and Data Lakehouse environments.
• Implement and optimize ETL/ELT processes for ingesting, transforming, and serving data from multiple business domains.
• Develop and maintain data processing solutions using Python, SQL, and Apache Spark.
• Support migration and modernization initiatives, including Unity Catalog adoption, platform upgrades, and data platform transformations.
• Build and maintain Databricks workflows, Delta Live Tables (DLT), metadata-driven frameworks, and orchestration processes.
• Collaborate with architects, analysts, and business stakeholders to translate business requirements into technical solutions.
• Ensure data quality, reliability, performance, and security across the data platform.
• Troubleshoot production incidents, perform root cause analysis, and implement corrective actions.
• Contribute to CI/CD implementation, infrastructure automation, monitoring, and operational best practices.
• Optimize data pipelines, storage structures, and processing workloads to improve efficiency and reduce costs.
• Participate in solution and architecture reviews while promoting engineering standards and governance principles.
• Support knowledge sharing, mentoring, and technical development within the team.
• Work closely with Data Architects and platform teams to ensure alignment with enterprise data architecture, Lakehouse principles, and governance requirements.
• Support reporting, analytics, and AI/ML initiatives by providing reliable and scalable data foundations.

Skills

Databricks

Azure Databricks

Apache Spark

Python

SQL

Azure Cloud

Data engineering

CI/CD

Delta Live Tables

Unity Catalog

Data governance

Data Lakehouse

Power BI

Stakeholder management

Tools

Azure Synapse Analytics

Azure Data Factory

Azure Data Lake

Azure DevOps

Job description

For our Partner we are looking for an experienced Senior Data Engineer.

The client operates in the travel and cruise industry, offering river, sea, and ocean voyages as well as expedition journeys. The company operates on a global scale, managing an extensive fleet and large volumes of data supporting operational, financial, reporting, and analytical processes.

Offer:

• Start: ASAP
• Engagement length: Long-term
• 100% Remote
• B2B (via Shimi)
• Rate up to 145 pln/h net+VAT

Important information:

• Minimum 5 years of commercial Databricks.
• Required English level: minimum B2+.
• Strong analytical and problem-solving skills.
• Ability to work independently with a high level of ownership and accountability.
• Proactive approach to identifying risks, blockers, and improvement opportunities.
• Strong communication and stakeholder management skills across technical and business teams.
• Experience working in dynamic environments with frequently changing priorities.
• Ability to make pragmatic decisions and deliver results despite incomplete requirements.
• Experience working within cross-functional teams.
• Understanding of data governance, security, compliance, and operational excellence.
• Comfortable working in an environment with a relatively low level of formal processes.
• Adaptable, resilient, and well-organized.
• Ability to independently drive initiatives and propose practical solutions.
• Thrives in a “controlled chaos” environment where flexibility, initiative, and self-organization are essential.

Technical requirements:

• Apache Spark
• Python
• SQL
• Azure Cloud
• Azure Databricks
• Azure Data Factory
• Azure Data Lake
• Azure Synapse Analytics
• Azure Data Explorer
• Databricks
• CI/CD
• Azure DevOps
• Power BI
• Experience in building and maintaining ETL/ELT processes
• Experience with Delta Live Tables (DLT)
• Experience with Unity Catalog
• Understanding of Lakehouse architecture
• Experience with infrastructure automation, monitoring, and logging

Responsibilities:

• Design, develop, and maintain scalable data solutions within the Azure Data Platform ecosystem, including Azure Synapse, Databricks, and Data Lakehouse environments.
• Implement and optimize ETL/ELT processes for ingesting, transforming, and serving data from multiple business domains.
• Develop and maintain data processing solutions using Python, SQL, and Apache Spark.
• Support migration and modernization initiatives, including Unity Catalog adoption, platform upgrades, and data platform transformations.
• Build and maintain Databricks workflows, Delta Live Tables (DLT), metadata-driven frameworks, and orchestration processes.
• Collaborate with architects, analysts, and business stakeholders to translate business requirements into technical solutions.
• Ensure data quality, reliability, performance, and security across the data platform.
• Troubleshoot production incidents, perform root cause analysis, and implement corrective actions.
• Contribute to CI/CD implementation, infrastructure automation, monitoring, and operational best practices.
• Optimize data pipelines, storage structures, and processing workloads to improve efficiency and reduce costs.
• Participate in solution and architecture reviews while promoting engineering standards and governance principles.
• Support knowledge sharing, mentoring, and technical development within the team.
• Work closely with Data Architects and platform teams to ensure alignment with enterprise data architecture, Lakehouse principles, and governance requirements.
• Support reporting, analytics, and AI/ML initiatives by providing reliable and scalable data foundations.