Senior Data Scientist

Accelerate your development and exposure to high‑performance data platforms and cloud infrastructure. Join Sedona Digital, a fast‑growing scale‑up with the ambition to be recognised as one of the leading technology companies in Romania. 

Our global client base needs builders, engineers who enjoy designing and implementing scalable data platforms, have deep expertise in cloud data technologies, and take pride in delivering reliable, well‑governed solutions. 

At Sedona, we: 

• Obsess about our customers 

• Build robust, scalable technical solutions 

• Create an open, collaborative culture 

• Invest in learning and long‑term careers 

We are looking for a Senior Data Engineer with strong experience in Azure‑based data platforms, including data lake and data warehouse architectures, orchestration with Azure Data Factory, and analytics using Azure Synapse and Power BI. The ideal candidate is comfortable working independently, making sound technical decisions, and supporting clients as they modernise their data estates. 

Responsibilities:

• Design, build, and maintain end‑to‑end data pipelines in Azure using Azure Data Factory, Azure Blob Storage / ADLS, and Azure Synapse Analytics. 

• Implement and maintain Azure‑based data lakes, including raw, staged, and curated layers, following agreed standards and best practices. 

• Design and optimise Azure Synapse Analytics environments, including table structures, distribution strategies, partitioning, and performance tuning. 

• Develop ingestion patterns for data sourced from on‑premises SQL Server, Azure SQL Database, other relational databases, and Cosmos DB. 

• Build secure and scalable orchestration workflows using Azure Data Factory for batch‑oriented data processing. 

• Implement secure authentication and access control using Azure Active Directory, ensuring proper role‑based access and least‑privilege principles. 

• Develop reusable, maintainable transformation logic aligned with agreed data modelling and semantic‑layer standards. 

• Support analytical workloads through integration with Azure Analysis Services and downstream consumption in Power BI. 

• Monitor, troubleshoot, and improve pipeline reliability, data quality, and platform performance. 

• Collaborate with architects, analysts, and client stakeholders to translate business requirements into scalable Azure data solutions. 

• Contribute to defining and enforcing data engineering standards, security practices, and governance patterns. 

• Support clients during platform adoption, knowledge transfer, and handover. 

• A relevant Microsoft Azure certification is required, or the successful candidate will complete one within the probation period. 

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 

• 5+ years of experience in data engineering, ETL/ELT development, and data integration. 

• Strong hands‑on experience with Microsoft Azure, including Azure Data Factory, Azure Blob Storage / ADLS, Azure Synapse Analytics, and Azure SQL. 

• Solid understanding of data lake and data warehouse architectures. 

• Experience designing and operating batch‑oriented data pipelines at scale. 

• Strong SQL skills and experience with data modelling (facts, dimensions, semantic layers). 

• Experience with Python or similar languages for data processing and automation. 

• Familiarity with Azure Active Directory and secure authentication patterns. 

• Ability to work independently, manage changing priorities, and make pragmatic technical decisions. 

• Strong communication skills in English, with the ability to explain technical concepts clearly. 

Preferred Skills (Nice to Have) 

• Experience with Azure Analysis Services, Power BI semantic models, or enterprise BI architectures. 

• Exposure to Synapse serverless SQL, lakehouse‑style patterns, or hybrid data platforms. 

• Familiarity with Databricks or Snowflake and ability to compare architectural trade‑offs. 

• Understanding of CI/CD practices for Azure data platforms. 

• Experience working in regulated or security‑sensitive environments. 

• Previous experience supporting discovery or early‑phase data platform design engagements.