Portuguese company hires for hybrid position
Location: Lisbon, Portugal
- ️ Only candidates already based in Portugal will be considered
Work Model: Hybrid
️ Language Requirements: English C1 — mandatory
Seniority: Senior (6+ years)
Sector: Banking
Rate Between €3900 - 4200 RV / €2500 – 2800 CTI
- ️ Instructions: Please send your CV in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success
We are looking for a Senior Data Engineer to design, implement, and support enterprise data solutions in a complex Data Warehouse and Big Data environment.
You will contribute to raw-data ingestion, data access, data quality, modelling, processing, integration, and production reliability. The role combines hands-on engineering with functional and technical analysis, documentation, testing, and collaboration with business and technology teams.
This opportunity is ideal for a data professional who understands the complete data lifecycle—from ingestion and transformation to modelling, reporting, deployment, and production support.
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Design and implement raw-data ingestion pipelines for Data Lake and Data Warehouse environments;
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Develop and maintain high-performance data pipelines;
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Implement data-access, data-referencing, integration, and quality processes;
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Work with batch and streaming data using technologies such as Kafka and NiFi;
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Develop data-processing solutions with Hadoop, Hive, Spark, Java, Scala, or Python;
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Create and optimise ETL processes, SQL, T-SQL, and Bash scripts;
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Design and maintain corporate data models;
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Analyse, plan, implement, and technically test Data Warehouse solutions;
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Ensure the industrialisation, monitoring, and production integration of data solutions;
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Maintain production-service commitments and investigate operational issues;
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Gather and analyse functional and technical requirements;
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Produce technical analyses, solution designs, test evidence, and decision documentation;
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Participate in quality certification and support User Acceptance Testing;
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Collaborate with business stakeholders and functional-analysis teams;
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Propose improvements to data platforms, tools, and engineering practices;
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Communicate technical decisions and ensure alignment with the data roadmap.
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More than six years of relevant professional experience in Data Engineering, Data Warehousing, Business Intelligence, or a similar field;
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At least four years of experience in functional or technical analysis and corporate data modelling;
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Strong experience with Data Warehouse solutions and their delivery lifecycle;
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Practical knowledge of the Hadoop ecosystem;
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Experience with data-access or exchange technologies such as Kafka or NiFi;
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Strong knowledge of SQL and NoSQL environments;
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Experience with ETL and data-pipeline development;
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Practical experience with at least one relevant programming language, such as Java, Scala, or Python;
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Experience with Hive, Spark, or similar large-scale data-processing technologies;
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Familiarity with Bash or other scripting languages;
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Knowledge of DevOps practices applied to data solutions;
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Experience with data quality, ingestion, integration, supervision, and production support;
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Ability to gather requirements and produce clear technical documentation;
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Experience working in Agile environments;
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English proficiency at C1 level;
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Availability to work in a hybrid arrangement in Lisbon;
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Bachelor’s or master’s degree in Computer Engineering, Information Technology, or a related discipline.
Candidates are not expected to demonstrate equal expertise in every language and platform listed. Strong Data Warehouse knowledge, data modelling, SQL, pipeline development, and meaningful exposure to the Hadoop ecosystem are the priorities.
Experience with the following technologies will be particularly valuable:
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Microsoft BI tools;
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SQL and T-SQL;
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Power BI;
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Jira;
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Confluence;
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Draw.io;
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Microsoft Excel and PowerPoint.
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Experience in Banking or Financial Services;
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Knowledge of consumer-credit processes;
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Experience supporting UAT and business certification;
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Knowledge of production monitoring and service commitments;
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Experience leading requirements or technical-analysis meetings;
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Familiarity with enterprise data governance;
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Experience improving or modernising data-management platforms.
The ideal candidate is a senior data professional who combines strong engineering capabilities with structured analytical and communication skills.
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Understand the full lifecycle of Data Warehouse and Big Data solutions;
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Can connect business requirements to appropriate data models and technical designs;
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Build reliable, maintainable, and observable data pipelines;
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Work confidently with structured, unstructured, batch, and streaming data;
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Consider data quality and production reliability throughout delivery;
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Document analyses, technical decisions, tests, and implemented solutions accurately;
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Communicate effectively with business and technical stakeholders;
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Investigate complex problems methodically;
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Work autonomously while maintaining alignment with team standards and roadmaps;
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Adapt to change and remain focused on customer and delivery outcomes.
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How many years of professional experience do you have in Data Engineering or Data Warehousing?
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How many years have you worked with functional or technical analysis?
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What experience do you have defining corporate data models?
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Which Data Warehouse solutions have you designed or supported?
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Have you worked across all phases of Data Warehouse delivery?
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What practical experience do you have with the Hadoop ecosystem?
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Which Hadoop-related technologies have you used?
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Have you developed pipelines with Spark or Hive?
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What experience do you have with Kafka or NiFi?
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Have you built raw-data ingestion pipelines for a Data Lake or Data Warehouse?
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Which programming languages do you use professionally: Java, Scala, Python, or others?
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What is your level of SQL and T-SQL expertise?
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Have you worked with NoSQL databases?
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What ETL tools and approaches have you used?
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How have you used Bash or scripting in data environments?
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What experience do you have with DevOps practices for data solutions?
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Have you monitored or supported data pipelines in production?
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How do you ensure data quality, traceability, and service reliability?
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What experience do you have with Microsoft BI tools and Power BI?
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Have you used Jira, Confluence, or Draw.io?
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Have you gathered requirements or led technical-analysis meetings?
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Have you supported quality certification or UAT?
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Do you have experience in Banking or consumer credit?
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What is your English proficiency level? Can you confirm C1?
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Are you currently based in or available to work in Lisbon?
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Are you comfortable with a hybrid working arrangement?
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Which contract model do you prefer: RV or CTI?
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Is the proposed rate aligned with your expectations?
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What is your earliest possible start date?
Senior Data Engineer, Data Engineer, Big Data Engineer, Data Warehouse Engineer, Data Warehouse Developer, Business Intelligence Engineer, Data Engineering, Big Data, Data Warehouse, Enterprise Data Warehouse, Data Lake, Raw Data Ingestion, Data Ingestion, Data Pipelines, High-Performance Data Pipelines, Batch Processing, Streaming Data, Hadoop, Hadoop Ecosystem, Apache Hadoop, Apache Spark, Spark, Apache Hive, Hive, Apache Kafka, Kafka, Apache NiFi, NiFi, Java, Scala, Python, Bash, Shell Scripting, ETL, ELT, SQL, T-SQL, NoSQL, Data Modelling, Data Modeling, Corporate Data Model, Logical Data Model, Physical Data Model, Data Access, Data Exchange, Data Integration, Data Quality, Data Referencing, Data Governance, Data Industrialisation, Production Integration, Pipeline Monitoring, Production Support, DevOps, Agile, Functional Analysis, Technical Analysis, Requirements Gathering, Technical Documentation, Technical Testing, Quality Assurance, UAT, Microsoft BI, Microsoft Business Intelligence, Power BI, Jira, Confluence, Draw.io, Banking, Financial Services, Consumer Credit, English C1, Lisbon, Portugal
#CI – RFC00059170
