Senior Data Engineer (Databricks Migration)
Warsaw, Masovian Voivodeship, Poland
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingMigrate ETL/ELT workloads from BigQuery to Databricks
Design Lakehouse architecture with Databricks and Delta Lake
Build and maintain PySpark pipelines across Bronze, Silver and Gold layers
Implement data governance and security with Unity Catalog
Troubleshoot and optimize complex SQL and Spark workloads
From the employer’s posting
Participate in the migration of a large-scale analytical platform from BigQuery to Databricks
Design and implement scalable Lakehouse architectures using Databricks and Delta Lake
Design and maintain medallion architecture layers including Bronze, Silver, and Gold
Implement data governance and security best practices using Unity Catalog
Troubleshoot and optimize complex SQL and Spark workloads
What you’ll bring
All qualificationsCore experience
- 5+ years as a Data Engineer
- Hands-on commercial experience with Databricks
- Strong Python and advanced SQL
- Strong Apache Spark knowledge, primarily PySpark
- Hands-on experience with Delta Lake
Qualification wording
5+ years of professional experience as a Data Engineer
Hands-on commercial experience with Databricks
Strong programming skills in Python and advanced SQL
Strong knowledge of Apache Spark, primarily PySpark
Hands-on experience with Delta Lake
Tools in this posting
- Python
- SQL
- AWS
- Azure
- BigQuery
- Databricks
- Delta Lake
- GCP
- Spark
- Airflow
- PySpark
Source — Tool mentions in context
- 5+ years of professional experience as a Data Engineer - Strong programming skills in Python and advanced SQL - Hands-on commercial experience with Databricks
As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform. Key Technologies: Databricks, Apache Spark, PySpark, Delta Lake, Python, SQL, Airflow, GCP, CI/CD, Unity Catalog
- Conduct code reviews and contribute to platform reliability and maintainability - Troubleshoot and optimize complex SQL and Spark workloads - Support production deployments and platform modernization activities
- Experience with Airflow or similar orchestration tools - Experience optimizing complex analytical SQL workloads - Experience implementing CI / CD practices for data engineering platforms
- Experience working with GCP cloud services - Experience with AWS or Azure cloud platforms - Experience in retail analytics or pricing optimization domains
Job Description - Participate in the migration of a large-scale analytical platform from BigQuery to Databricks - Design and implement scalable Lakehouse architectures using Databricks and Delta Lake
Are you a Senior Data Engineer passionate about building scalable, high-performance data platforms and working with modern Lakehouse technologies? Join Sigma Software’s Data Engineering Center of Excellence and contribute to the modernization of an enterprise-scale analytics ecosystem for the retail domain. We are looking for a Senior specialist with strong Databricks, PySpark, and cloud data engineering expertise to participate in the migration of a large-scale analytical platform from BigQuery to Databricks. You will collaborate with international teams, contribute to architectural decisions, and help shape reliable and scalable data solutions. We at Sigma Software create opportunities for continuous learning, technology growth, and meaningful engineering impact while working on complex international projects.
PROJECT The project focuses on the strategic migration of a large-scale analytical platform from a legacy BigQuery ecosystem to a modern Databricks Lakehouse architecture. The platform processes high-volume retail datasets, machine learning workloads, analytics pipelines, and customer-specific business logic. As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform.
- Participate in the migration of a large-scale analytical platform from BigQuery to Databricks - Design and implement scalable Lakehouse architectures using Databricks and Delta Lake - Analyze existing ETL / ELT workloads and define migration approaches
- Strong programming skills in Python and advanced SQL - Hands-on commercial experience with Databricks - Strong knowledge of Apache Spark, primarily PySpark
- Experience developing ETL / ELT pipelines and large-scale data processing solutions - Hands-on experience with Delta Lake - Experience with Spark Declarative Pipelines
The project focuses on the strategic migration of a large-scale analytical platform from a legacy BigQuery ecosystem to a modern Databricks Lakehouse architecture. The platform processes high-volume retail datasets, machine learning workloads, analytics pipelines, and customer-specific business logic. As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform. Key Technologies: Databricks, Apache Spark, PySpark, Delta Lake, Python, SQL, Airflow, GCP, CI/CD, Unity Catalog
WILL BE A PLUS - Experience working with GCP cloud services - Experience with AWS or Azure cloud platforms
- Implement incremental processing strategies and scalable transformation frameworks - Build and maintain Spark-based data processing solutions using PySpark - Design and maintain medallion architecture layers including Bronze, Silver, and Gold
- Hands-on commercial experience with Databricks - Strong knowledge of Apache Spark, primarily PySpark - Experience designing and building modern cloud-based data platforms
- Hands-on experience with Delta Lake - Experience with Spark Declarative Pipelines - Experience with cluster monitoring, metrics analysis, and performance optimization
- Solid understanding of data warehousing concepts and dimensional modeling - Experience with Airflow or similar orchestration tools - Experience optimizing complex analytical SQL workloads
Posting record
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- Live
- First seen by us
- Aug 11, 2026 · 79 days ago
- Recorded sightings
- 270
- Last seen by us
- Oct 29, 2026
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Job description
Job Description
- Participate in the migration of a large-scale analytical platform from BigQuery to Databricks
- Design and implement scalable Lakehouse architectures using Databricks and Delta Lake
- Analyze existing ETL / ELT workloads and define migration approaches
- Develop and optimize data pipelines processing large volumes of retail and analytical data
- Implement incremental processing strategies and scalable transformation frameworks
- Build and maintain Spark-based data processing solutions using PySpark
- Design and maintain medallion architecture layers including Bronze, Silver, and Gold
- Implement data governance and security best practices using Unity Catalog
- Collaborate with Data Science, Analytics, Product, and Customer Engineering teams
- Participate in architecture discussions and technical solution design
- Develop reusable data platform components and engineering standards
- Conduct code reviews and contribute to platform reliability and maintainability
- Troubleshoot and optimize complex SQL and Spark workloads
- Support production deployments and platform modernization activities
Qualifications
- 5+ years of professional experience as a Data Engineer
- Strong programming skills in Python and advanced SQL
- Hands-on commercial experience with Databricks
- Strong knowledge of Apache Spark, primarily PySpark
- Experience designing and building modern cloud-based data platforms
- Experience developing ETL / ELT pipelines and large-scale data processing solutions
- Hands-on experience with Delta Lake
- Experience with Spark Declarative Pipelines
- Experience with cluster monitoring, metrics analysis, and performance optimization
- Strong understanding of distributed data processing architectures
- Solid understanding of data warehousing concepts and dimensional modeling
- Experience with Airflow or similar orchestration tools
- Experience optimizing complex analytical SQL workloads
- Experience implementing CI / CD practices for data engineering platforms
- Strong troubleshooting and performance optimization skills
- Ability to work collaboratively in cross-functional international teams
- Upper-Intermediate or higher English level
WILL BE A PLUS
- Experience working with GCP cloud services
- Experience with AWS or Azure cloud platforms
- Experience in retail analytics or pricing optimization domains
- Experience supporting machine learning or AI-related data workloads
- Experience with platform modernization and cloud migration initiatives
Additional Information
PERSONAL PROFILE
- Strong analytical and problem-solving mindset
- Proactive and ownership-driven approach
- Ability to work independently and collaboratively
- Good communication and stakeholder collaboration skills
- Passion for scalable data engineering and modern data platforms
- Interest in continuous learning and technology innovation
Company Description
Are you a Senior Data Engineer passionate about building scalable, high-performance data platforms and working with modern Lakehouse technologies? Join Sigma Software’s Data Engineering Center of Excellence and contribute to the modernization of an enterprise-scale analytics ecosystem for the retail domain.
We are looking for a Senior specialist with strong Databricks, PySpark, and cloud data engineering expertise to participate in the migration of a large-scale analytical platform from BigQuery to Databricks. You will collaborate with international teams, contribute to architectural decisions, and help shape reliable and scalable data solutions.
We at Sigma Software create opportunities for continuous learning, technology growth, and meaningful engineering impact while working on complex international projects.
CUSTOMER
Our Customer is a leading retail technology company specializing in AI-driven pricing optimization solutions for enterprise retailers. The company helps businesses improve profitability and competitiveness through advanced analytics, automation, and intelligent pricing strategies. Their platform combines business intelligence with sophisticated algorithms to support data-informed pricing decisions at scale for global retail organizations.
PROJECT
The project focuses on the strategic migration of a large-scale analytical platform from a legacy BigQuery ecosystem to a modern Databricks Lakehouse architecture. The platform processes high-volume retail datasets, machine learning workloads, analytics pipelines, and customer-specific business logic.
As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform.
Key Technologies: Databricks, Apache Spark, PySpark, Delta Lake, Python, SQL, Airflow, GCP, CI/CD, Unity Catalog
Source details
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- Location & working pattern
Warsaw, Masovian Voivodeship, Poland
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