Junior Data Ops / Analytics Engineer [Málaga] New

Description

Job Summary: We are seeking a candidate with a strong technical foundation in data engineering, focused on data quality and information structuring to enable advanced analytics and AI initiatives. Key Highlights: 1. Develop and maintain ETL/ELT processes using Python and SQL 2. Integrate and consolidate data from multiple sources 3. Design and maintain relational data models Location: Málaga – Hybrid mode (3 days onsite per week) We seek a candidate with a solid technical background in data engineering, oriented toward data quality and information structuring, who contributes to enabling advanced analytics and artificial intelligence initiatives by building reliable and well-modeled datasets. ### **Key Responsibilities:** * Develop and maintain production ETL/ELT processes using Python, SQL, and SAS. * Integrate and consolidate data from multiple sources, ensuring coherence, consistency, and traceability. * Implement data cleaning, normalization, and validation processes. * Design and maintain normalized relational data models and optimized analytical structures. * Build datasets and analytical tables prepared for consumption by artificial intelligence models. * Document transformations, business rules, and data structures, collaborating with analytical and technical teams to translate functional requirements into technical solutions. ### **Requirements:** **Mandatory:** * At least one year of experience in roles related to Data Ops, Analytics Engineering, Data Engineering, or similar. * Experience with **SAS**. * Solid knowledge of **Python** for data processing, transformation, and manipulation. * Advanced proficiency in **SQL** (complex joins, subqueries, aggregations, window functions). * Experience developing and maintaining production **ETL** processes. * Knowledge of relational data modeling and normalization principles. * Experience working with medium- or large-scale data volumes. * Proficiency with version control systems (Git). * Conceptual understanding of machine learning models (explanatory variables, target variable, temporal windows) and the impact of data quality on model performance. **Desirable:** * Knowledge of analytical architectures (Data Lake, Data Warehouse). * Experience with data pipeline orchestration tools. * Familiarity with analytical data formats. * Basic knowledge of cloud environments or distributed data platforms. * Understanding of the lifecycle of analytical solutions in production. ### **We Offer** * Permanent contract with competitive salary * Flexible work mode and possibility of remote work. * Personalized career plan and continuous training (certifications, English, etc.). * Participation in stable projects with a high technical component. * Flexible working hours and focus on work-life balance. * Social benefits tailored to your needs We invite you to get to know us at http://www.neoris.com, Facebook, LinkedIn, Twitter or Instagram: @NEORIS. \#LI\-MM4