Senior Analytics Engineer

Data Science UA

is a service company with strong data science and AI expertise. Our journey began in 2016 with the uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:

It is a new generation of data service provider, specializing in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organizations. The broad range of data-driven solutions in data consulting and digital marketing are designed to meet clients' specific needs, always conceived with a business-centric approach and delivered with tangible results.

About the role:

We are seeking a highly skilled Senior Analytics Engineer to drive the end-to-end lifecycle of data products. You will act as the technical bridge between raw data sources and advanced data science, utilizing Microsoft Azure
 technologies to drive data discovery, innovation, and the deployment of scalable analytical solutions. You will play a pivotal role in implementing 
Data Fabric
 architectures to "stitch" together disparate data sources—creating a unified, accessible view of the consumer without the bottlenecks of traditional rigid silos.

Key Responsibilities:

- Azure Cloud Architecture & Engineering:

Design and maintain scalable data pipelines and analytical environments using the Azure stack (e.g., Azure Synapse, Data Factory, Databricks, Azure SQL). Ensure optimal performance and cost-efficiency of cloud resources.

- Data Fabric Implementation:

Champion the adoption of Data Fabric principles to connect data across on-premise and multi-cloud environments. Implement logical data layers and virtualization techniques to provide seamless data access without unnecessary data movement.

- Data Integration & Modeling:

Design robust, modular data models. Integrate fragmented data sources across multiple markets to create a "single source of truth" while utilizing active metadata management to automate data delivery.

- Data Strategy & Innovation:

Drive data discovery initiatives to identify new value drivers. Architect innovative data products that solve complex business challenges using modern data mesh or fabric methodologies.

- Data Science Collaboration:
 Prepare high-quality, feature-rich datasets. Partner closely with Data Scientists to explain data nuances and lineage, ensuring the data foundation supports advanced modeling and machine learning.

- 
Domain Expertise:
 Apply deep knowledge of consumer data domains—specifically Loyalty, Promotions, Subscriptions, and E-commerce—to ensure analytical solutions are business-relevant and actionable.

Required Qualifications:

- Technical Proficiency:

Expert-level proficiency in SQL and Python is required.

- Azure Expertise:

Proven experience in cloud data warehousing and engineering within the Microsoft Azure ecosystem
 (Synapse Analytics, Azure Data Lake Gen2, Azure Data Factory).

- 
Data Fabric & Virtualization:

Strong understanding of Data Fabric concepts, including data virtualization, active metadata management, and knowledge graphs (experience with tools like Microsoft Purview or logical data warehousing is a plus).

- Data Modeling:

Advanced experience in dimensional modeling and building performant data marts.

- Consumer Data Experience:

Strong experience working with consumer-centric data (Loyalty, CRM, E-commerce).

- Communication:

Ability to translate complex technical data concepts for non-technical stakeholders and Data Scientists.

We offer:

- Free English classes with a native speaker and external courses compensation.

- PE support by professional accountants.

- 40 days of PTO.

- Medical insurance.

- Team-building events, conferences, meetups, and other activities.

- There are many other benefits you'll find out at the interview.