Data & AI Platform / Solution Architect

Location : MUST BE IN PORTUGAL

Hybrid Position : 2 / 3 times per week in Client (Lisbon)

• Deliverables :

Model business requirements - data-related - in a standardized, denormalized, star, or other data model according to the objectives.

Model business requirements in a data model beyond tabular : columnar, graph, geographic, time series, document.

Model business requirements including data streams and integrations (schema API, CRUD API).

Design the data model and data architecture to meet qualitative requirements : price, write / get performance (indexed queries), scans, and feature retrieve (advanced queries for analytics), and elasticity of use (scale up, scale out, pause).

Design and implement reference data architectures according to the data management strategy requirements.

Design and implement a blueprint for an organizational data framework that defines how data is obtained, stored, consumed, integrated, and managed to enrich the company's Data Lakes, MDUs, and Data Marts.

Define indicators inherent to DataOps observability, organized into three aspects :

o Operational health of the data pipeline (duration, delay, retires, duration between subsequent executions)

o Dataset-level health (availability, freshness, volume, data schema changes)

o Data-level health (profiling within the "expectation envelope", outlier and anomaly detection, data drift, and business rule enforcement)

Ensure technical functionalities (e.g., scalability, security, performance, data recovery, reliability, etc.)

Apply best practices for data governance and data security : data catalog, data lineage, data quality, master data management, metadata management, data standards

Strategic design and harmonization between organizational architecture, systems architecture, data architecture, technology architecture, and the business vision.

Standardized design in accordance with regulatory aspects regarding data use.

Preparation of business process reports;

Implementation of corrections and improvements to the Celonis platform;

Technical functional analyses for the inclusion of new processes in Celonis.

Must have :

Degree in Software Engineering or Computer Engineering or similar

Knowledge of the Energy & Utilities market and GDPR

Experience in strategic projects

Up-to-date knowledge of databases and analytical technologies, including data lake / lakehouse architectures and NoSQL storage.

Experience with Cloud Platforms (one or more : AWS, Google, Azure)

Knowledge of data governance and data security practices

Knowledge of Machine Learning, algorithms, and statistical models (such as classification, time series analysis, regression, etc.)

Experience with metadata management, data catalogs, data standards, and master data management best practices

Experience with BigData databases (one or more : BigQuery, Azure Synapse, AWS RedShift, Cassandra, Couchbase, HDFS);

Certification – CELONIS;

Proven experience in technology implementations – CELONIS;

Implement the technical data stewardship, ensuring a holistic data scanning and data lineage from the main operational and analytics applications;

Implement global initiatives to improve overall data quality, with a focus on common challenges faced by multiple business platforms;

Provide centralized training programs and communication strategies to ensure that data governance best practices are understood and followed consistently across all business platforms;

Implement monitoring mechanisms to track data quality, consistency, and adherence to policies across the organization.