Data & Analytics Engineering (QuickSight Environment)
⚲ Lisbon
Do uzgodnienia
Wymagania
- Microsoft SQL Server
- Business Intelligence (BI)
- Operations
- Artificial Intelligence (AI)
- DataStage (ETL)
- SQL
- Python
- Data modeling
- ETL
- SQL Server Integration Services (SSIS)
Opis stanowiska
We are looking for a Data & Analytics Engineer to join our team.
The focus is predominantly on Data & Analytics Engineering (backend), with limited exposure to reporting and dashboarding (frontend — QuickSight vs QlikView) for those who join.
Responsibilities:
• 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.
• Support the team with data sets/products for building, 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
• Proactively propose process optimizations, make timely data-driven decisions, and demonstrate resilience through change.
Qualifications:
• Senior 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.
• 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 (ability to engage stakeholders in both languages)
The focus is predominantly on Data & Analytics Engineering (backend), with limited exposure to reporting and dashboarding (frontend — QuickSight vs QlikView) for those who join.
Responsibilities:
• 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.
• Support the team with data sets/products for building, 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
• Proactively propose process optimizations, make timely data-driven decisions, and demonstrate resilience through change.
Qualifications:
• Senior 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.
• 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 (ability to engage stakeholders in both languages)
🔍 Dekoder Ogłoszenia
🔴
The focus is predominantly on Data & Analytics Engineering (backend), with limited exposure to reporting and dashboarding (frontend — QuickSight vs QlikView) for those who join.
Chociaż ogłoszenie wspomina o QuickSight, rola skupia się głównie na backendzie, a frontend (tworzenie raportów i dashboardów) będzie marginalny.
🔴
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.
Oczekuje się szerokiego zakresu wiedzy i umiejętności w obszarze danych, od modelowania po strategię architektoniczną, co może oznaczać dużą odpowiedzialność.
🔴
Leverage cutting-edge cloud technologies such as AWS (preferable) and Azure and data warehouses
Wymagane jest doświadczenie z konkretnymi technologiami chmurowymi, co może oznaczać, że firma nie zapewnia szkoleń w tym zakresie.
🔴
Deliver projects safely, on time, and cost effectively while upholding IT governance
Oznacza to, że projekty muszą być realizowane zgodnie z ustalonymi procedurami i budżetem, co może ograniczać elastyczność.
🔴
Proactively propose process optimizations, make timely data-driven decisions, and demonstrate resilience through change.
Oczekuje się inicjatywy w usprawnianiu procesów i adaptacji do zmian, co może oznaczać nieustanne wprowadzanie nowych rozwiązań i wymagań.