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Senior Analytics Engineer

Tagus Park

Job description

To integrate the Customer Intelligence department, the client is looking for a Senior Analytics Engineer.

Tasks:
Design, implement, and ensure the maintenance of new analytical data models that synthesize complex customer, operational, and digital behavior data into actionable formats for the following applications: exploratory analysis, reporting, and AI model development;
Diagnose and migrate ETL processes to modern and cloud-based applications. Migrate locally orchestrated SAS processes in cron jobs to a cloud system, aligned with the development practices of the central Data Engineering team;
Monitor and improve the performance of data pipelines, focusing on creating robust alarm systems that allow for proactive responses;
Establish best practices and frameworks for data model governance, documentation (data dictionary, process lineage), and quality control, ensuring alignment with the central Data Engineering team;
Proactively identify business opportunities for automation and enrichment of data models. Collaborate with other teams to identify automation of scripts, creation of new features for ML model training, automation of insights, etc.


Requirements

Bachelor's or Master's/Postgraduate degree in Business Intelligence, Enterprise Data Warehouse, Computer Engineering, or related fields;
5+ years of experience in Data Engineering, preferably in the banking sector;
Experience with modern data warehouse technologies (e.g., Starburst, Snowflake, BigQuery, etc.);
Experience in effective collaboration with data partners (e.g., Data Analysts, Data Scientists, etc.);
Knowledge of data modeling techniques (e.g., star schema, dimensional modeling);
Experience in leading and executing Data Engineering projects, with a focus on ETL process migrations, and demonstrated tangible and measurable business impact;
Proficiency in SQL and experience in designing efficient database schemas;
Basic knowledge of SAS language for use cases related to code migrations.

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