Data Analyst job opportunity at Adidas.

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Adidas Data Analyst
Experience: 1-years
Pattern: full-time
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degreeAssociate
loacation Porto, 13, , Portugal
loacation Porto, 13, ....Portugal

Purpose & Overall Relevance for the Organization: Data engineer builds and optimizes the systems that allow to perform proper analytics. They are responsible for the accuracy of the data as well as making it accessible to individuals who need to work with it. The data engineer ensures that any data is properly received, transformed, stored, and made accessible to other users. This role is to be a key contributor in building the adidas data lakehouse platform by designing and developing tools that enable adidas data engineers to explore, integrate, and prepare various internal and external data sources for consumption in a lakehouse environment. This work will support the creation of an integrated Data & AI lakehouse platform, connecting hundreds of data sources (e.g., Kafka, SAP, REST APIs) to thousands of consumers. You will collaborate with other data engineers and senior management to deliver the best data engineering experience within the adidas data lakehouse. Key Responsibilities: Analytics • Undertakes analytical activities and delivers analysis outputs, in accordance with customer needs and conforming to agreed standards. Emerging technology monitoring • Supports monitoring of the external environment and assessment of emerging technologies to evaluate the potential impacts, threats, and opportunities to the organization. • Contributes to the creation of reports, technology road mapping and the sharing of knowledge and insights. Data modelling & design • Investigates corporate data requirements, and applies data analysis, design, modelling, and quality assurance techniques, to establish, modify or maintain data structures and their associated components (entity descriptions, relationship descriptions, attribute definitions). • Provides advice and guidance to database designers and others using the data structures and associated components. Database design • Develops and maintains specialist knowledge of database and data warehouse concepts, design principles, architectures, software, and facilities. • Assesses proposed changes to object/data structures, to evaluate alternative options. • Implements physical database designs to support transactional data requirements for performance and availability. • Implements data warehouse designs that support demands for business intelligence and data analytics. Programming/software development • Designs, codes, verifies, tests, documents, amends, and refactors complex programs/scripts and integration software services. • Contributes to selection of the software development approach for projects, selecting appropriately from predictive (plan-driven) approaches or adaptive (iterative/agile) approaches. • Applies agreed standards and tools, to achieve well-engineered outcomes. • Participates in reviews of own work and leads reviews of colleagues' work. Testing • Reviews requirements and specifications and defines test conditions. • Designs test cases and test scripts under own direction, mapping back to pre-determined criteria, recording and reporting outcomes. • Analyses and reports test activities and results. • Identifies and reports issues and risks associated with own work. Data management • Assists in providing accessibility, retrievability, security and protection of data in an ethical manner. Requisite Education and Experience / Minimum Qualifications: • Four-year college or university degree with focus on Business Administration or IT or related areas, or equivalent combination of education and experience • Proficient spoken and written command of English • 1+ years of hands-on data engineering experience • A developer capable of creating state-of-the-art data applications using Python and SQL • Understanding of Spark, Delta lake and its internals • Knowledge of cloud platforms, data modeling, batch & streaming ETL, and databases • Experience with software engineering best practices (e.g., design patterns, test-driven development, clean code)

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