O stanowisku

An Azure Data Architect designs and implements data solutions using Microsoft Azure technologies to support enterprise data management, analytics, and business intelligence initiatives.

Lingaro

At Lingaro, we empower global brands to achieve more with data. We lead our clients, from strategy through development to operations and adoption, transforming data into opportunities that propel their business’ forward. More than 1600 experts around the globe working remotely, blend technology excellence with deep business knowledge to create user centric solutions simplifying data complexity and unlocking value. Everything based on the collaborative culture with openness for no barriers approach and autonomy to take ownership. We are certified as the Great Place To Work® company in Poland, the Philippines and India.

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Czy do nas pasujesz?

Proven experience with Microsoft Azure services for data, such as Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database.
Strong knowledge of data modeling, database design, and data warehousing concepts.
Proficiency in ETL/ELT processes, data integration techniques, and scripting languages like SQL, Python, or Spark.
Understanding of data security, privacy regulations, and compliance frameworks (e.g., GDPR, HIPAA).
Excellent analytical, problem-solving, and communication skills for cross-functional collaboration.
Relevant certifications like Microsoft Certified: Azure Data Engineer or Azure Solutions Architect are often preferred.

Czym się zajmiesz

Design scalable and secure data architectures on Azure platforms, including data lakes, warehouses, and databases.
Implement and manage data pipelines using Azure Data Factory, Synapse Analytics, and related services.
Collaborate with data engineers, analysts, and stakeholders to translate business requirements into technical data solutions.
Ensure data governance, compliance, and security standards are met across all data systems.
Optimize data storage, processing, and performance for cost efficiency and reliability.
Develop and maintain documentation for data architectures, processes, and best practices.