Data Analytics Engineer
Job Summary
The Data & Analytics Engineer will partner with cross-functional stakeholders to identify high-impact use cases and implement advanced data architecture strategies. This role involves building and maintaining self-service analytics, data lakes, and data mesh concepts to support machine learning and business intelligence. You will leverage cloud technologies like AWS and Azure to deliver scalable, reliable data products while ensuring compliance with GMP and HSE standards.
Responsibilities
- Partner with stakeholders to identify high-impact use cases
- Build and maintain data lake/mesh and self-service analytics
- Engineer features and preprocess structured/unstructured data
- Implement machine learning models and data products
- Ensure compliance with GMP, HSE, and IT governance
Required Skills
- 4+ years in data management and analytics
- Advanced SQL and Python proficiency
- Cloud data architecture (AWS/Azure)
- Data modeling and visualization (QuickSight/PBI/Qlik)
- Experience with Git and Agile/SCRUM
Job Details
Responsibilities:
- Partner with stakeholders across functions as a data business partner, identifying high impact use cases and areas for improvement.
- Apply database modeling and database exploration skills with data architecture strategy and design principles to support metrics, analytics, AI/machine learning, and self-service business intelligence across the company.
- Build, standardize, and maintain reporting and self-service analytics as part of data lake and data mesh concepts.
- Preprocess and engineer features from structured and unstructured data, ensuring quality, lineage, and reliability.
- Analyze data from multiple sources to optimize strategies, operations, and portfolio decisions.
- Implement models and data products with cross functional teams; set up monitoring, alerting, and lifecycle management.
- Leverage cutting-edge cloud technologies such as AWS (preferable) and Azure and data warehouses.
- Communicate insights clearly through compelling visualizations and narratives tailored to technical and business audiences.
- Deliver projects safely, on time, and cost effectively while upholding IT governance, GMP/HSE, and compliance standards (COPs, SOPs).
- Proactively propose process optimizations, make timely data-driven decisions, and demonstrate resilience through change.
Required Qualifications:
- University degree in Computer Science, Engineering, Mathematics or a similar scientific field.
- 4+ years of experience in data management and data analytics with considerable experience in manipulating large datasets and data products.
- Strong autonomy to lead analytic solutions from design to deployment; and strong foundation in analytics framework and data management.
- Strong experience with cloud data-lake architecture and technology, in particular AWS; familiarity with Python data processing libraries; knowledge of IaC is a plus.
- Advanced proficiency in SQL and Python; familiarity with R and object-oriented scripting is a plus.
- Strong experience with Git for version control, including branch management, code reviews, and collaborative workflows in agile teams is a plus.
- Hands-on experience with SQL Server Integration Services (SSIS) for ETL/data integration workflows is a plus.
- Solid data modeling and experience in data visualization and reporting technologies-especially AWS QuickSight (preferable), MS Fabric/PBI or QlikSense.
- Exceptional communication and mediation skills with the ability to influence and engage stakeholder and ability to understand technical concepts and turn them into business terms.
- Familiarity with agile work methodologies (e.g. SCRUM).
- Fluency in English is a requirement; Portuguese proficiency strongly preferred.
- Knowledge of GMP (even high-level), data governance, and safe-by-design practices; team player with resilience and a long-term mindset.