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What you’ll bring

All qualifications

Core experience

5+ years of professional experience as a Data Engineer
Strong knowledge of Apache Spark, primarily PySpark
Ability to work collaboratively in cross-functional international teams
Experience working with GCP cloud services
Experience designing and building modern cloud-based data platforms
Experience with AWS or Azure cloud platforms

Qualification wording

5+ years of professional experience as a Data Engineer

Strong knowledge of Apache Spark, primarily PySpark

Ability to work collaboratively in cross-functional international teams

Experience working with GCP cloud services

Experience designing and building modern cloud-based data platforms

Experience with AWS or Azure cloud platforms

Tools in this posting

Python
SQL
AWS
Azure
BigQuery
Databricks
Delta
Google Cloud (GCP)
Spark
Airflow
PySpark

Source

- 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

Job description

View original posting ↗

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

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Kyiv, Kyiv city, Ukraine

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First seen by us: Aug 11, 2026
Recorded sightings: 159
Last seen by us: Sep 25, 2026

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Senior Data Engineer (Databricks Migration)