Senior Data Engineer – Data Platform & Analytics (M/F/D)

Icligo; Vila Nova de Gaia; On-site; EUR 55,000 - 75,000; Full time

Job summary

iCliGo seeks a Senior Data Engineer to design and implement a company-wide data platform. You will oversee data ingestion, transformation, and delivery of analytical models, KPIs, and dashboards across multiple business domains.

You will build scalable ETL/ELT pipelines, define dimensional models, and power dashboards with Power BI or similar tools, ensuring data quality and governance across the organization.

Qualifications

• 4+ years in Data Engineering, Analytics Engineering, or related roles.
• Experience building or evolving data platforms.
• Strong SQL/NoSQL skills and Python for data processing.
• Experience with ETL/ELT pipelines and data lake/warehouse architectures.
• Ability to translate business needs into data models and analytics solutions.

Responsibilities

• Design and implement the data platform architecture (Data Lake/Warehouse/Lakehouse).
• Build and维护 data ingestion and transformation pipelines from multiple sources.
• Integrate data from relational and NoSQL databases, APIs, and files.
• Develop scalable ETL/ELT processes and analytical data models.
• Collaborate with teams to define metrics and KPIs and power dashboards.
• Ensure data quality, lineage, and observability across pipelines.

Skills

SQL

NoSQL

Python

ETL/ELT

Data Lake

Data Warehouse

Lakehouse

Data Modeling

Data Integration

Cloud Platforms

Data Quality

Observability

Git & CI/CD

Communication

Tools

Power BI

Apache Superset

Metabase

Looker

Tableau

Job description

At iCliGo, we are building the next generation of our data platform to support business, product, operations, marketing, and technology decisions with reliable, integrated, and actionable information. We are looking for a Senior Data Engineer – Data Platform & Analytics to help us design and implement this data foundation, from data ingestion and transformation to the delivery of analytical models, KPIs, and dashboards. The goal is not simply to build reports. We want to build a company-wide data platform capable of consolidating information from our applications, bookings, suppliers, payments, operations, marketing, support, and other sources, creating a true single source of truth for iCliGo.

Key Responsibilities

• Design and implement the architecture of our data platform, including Data Lake, Data Warehouse, or Lakehouse solutions.
• Build and maintain data ingestion and transformation pipelines from multiple sources.
• Integrate data from relational and NoSQL databases, APIs, files, external systems, and event streams.
• Develop scalable, automated, and observable ETL/ELT processes.
• Build analytical data models designed for reporting, Business Intelligence, and advanced analytics.
• Define and implement dimensional models, fact tables, dimensions, and analytical datasets.
• Work closely with Product, Technology, Marketing, Finance, Operations, and other teams to define metrics and KPIs.
• Build the data layer required to power dashboards and reporting.
• Develop and support the creation of dashboards and analytical models using Power BI, Apache Superset, or equivalent tools.
• Ensure data quality, consistency, traceability, and integrity.
• Implement monitoring and validation mechanisms for pipelines and datasets.
• Establish best practices around Data Quality, Data Lineage, Data Governance, and Data Observability.
• Document data sources, models, transformations, metrics, and their lineage.
• Build a centralized and consistent metrics layer across different areas of the business.
• Support exploratory analysis and the identification of trends, issues, and opportunities.
• Prepare the data platform for future Analytics, Machine Learning, and AI use cases.
• Contribute to the definition and evolution of iCliGo's data strategy and architecture.

What We're Looking For

• 4+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or similar roles.
• Relevant experience building or evolving data platforms.
• Strong experience with SQL and NoSQL.
• Experience using Python for data processing, transformation, and automation.
• Experience building and operating ETL/ELT pipelines.
• Experience with Data Lakes, Data Warehouses, or Lakehouse architectures.
• Strong knowledge of data modelling for analytics.
• Experience integrating data from different systems and formats.
• Experience working with cloud platforms.
• Experience with Business Intelligence and Data Visualization tools such as Power BI, Apache Superset, Metabase, Looker, Tableau, or equivalent.
• Knowledge of batch, near-real-time, and event-driven architectures.
• Experience with version control, Git, and CI/CD practices.
• Strong focus on data quality, reliability, and observability.
• Ability to translate business needs into data models, metrics, and analytical solutions.
• Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.
• Autonomy, critical thinking, and the ability to thrive in a growing technology environment.