Data Architect

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UST is searching for a Data Architect who will develop and implement an overall data strategy aligned with the data pipeline. The strategy includes model design, database development standards, integration specifications, data warehouse implementation management, and systems analytics.

The opportunity:

·       Create patterns that data engineers can use to improve data ecosystems.

·       Draw blueprints for the data framework architecture, including the principles and standards followed by developers and engineers.

·       Document requirements for other departments regarding proper data management, including both data generating and data consuming departments.

·       Identify internal and external data sources and develop a data management plan aligned with the Data Office team's strategy.

·       Coordinate and collaborate with functional teams, stakeholders, and vendors to ensure smooth operation of data systems.

·       E2E management of data architecture, from platform selection, technical architecture design, final application development, testing, and solution implementation.

·       Plan and execute Big Data solutions using technologies such as GCP, Hadoop, Hive, Airflow, etc., ensuring the complete lifecycle of each solution.

·       Define and manage data flow and information dissemination within the organization.

·       Integrate technical functionalities, ensuring accessibility, accuracy, and security.

·       Conduct continuous audits of data management system performance, improving where necessary, and immediately reporting any non-compliance or gaps to stakeholders.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

What you need:

·       Minimum 6 years of experience, including 2 years as a Data Architect, with a degree in computer science, information systems, or another related field (data science, mathematics, statistics). Advanced knowledge in data warehouse design and implementation.

·       Extensive knowledge in the design and implementation of enterprise data lakes.

·       Extensive knowledge of Snowflake, Kafka, AWS, Azure, GCP, and Cloud data architecture.

·       Demonstrated knowledge of managing large data sets and relational and non-relational databases.

·       Knowledge and experience working with ETL processes and data acceleration technologies.

·       Knowledge and experience with scalable, distributed, and reliable software.

·       Strong communication skills, particularly those with a high level of technical knowledge for non-technical audiences.

·       Strong skills in short- and long-term project management and follow-up.

·       Experience using data flow and extraction tools such as Airflow and Big Query.

·       Experience with agile frameworks. English B1–B2