Job Type: Permanent
Work Mode: Hybrid (3 Days from office)
Job Description
As Senior Data Engineer, you will design, build and evolve secure, scalable and governed data solutions that enable to deliver reliable controls, regulatory outcomes and actionable client, income, commercial, or control insights. You will combine deep hands-on engineering expertise with end-to-end ownership, translating business and regulatory needs into robust data models, pipelines and business intelligence solutions. You will be a senior technical contributor across strategic data, BI and AI initiatives. You are expected to be visible, pragmatic and closely involved in delivery, from solution design and engineering through testing, deployment and production support. You will raise engineering standards, anticipate risks, provide clear technical direction and help the team deliver consistently without surprises. As a senior member of the team, you will share best practices, coach colleagues and contribute to a solution-focused, collaborative culture anchored in the Orange Code behaviours. This role reports functionally into the Data Domain Area lead in Amsterdam and hierarchically to the Change Lead.
As a Senior Data Engineer, you play a pivotal role in driving data engineering, data insights, BI and AI projects through empowered teams and strategic alignment. Your key responsibilities include:
- Own the end-to-end design, development and maintenance of scalable data pipelines and data products, covering ingestion, transformation, storage, orchestration and consumption. - Translate business, control and regulatory requirements into robust technical designs, governed data models and fit-for-purpose BI solutions.
- Design and implement reliable ETL and ELT processes for batch and, where relevant, streaming workloads, with appropriate controls for data quality, lineage and traceability. - Lead technical solution design and provide reusable blueprints that improve scalability, maintainability, client outcomes and regulatory compliance.
- Build engineering quality into delivery through automated testing, code review, version control, CI/CD, monitoring, observability and clear operational ownership.
- Own the deployment lifecycle for new and changed data models and BI solutions across test, acceptance and production environments.
- Perform impact assessments and work with cross-functional partners to evaluate business, operational, process and technology implications before implementation.
- Partner with analysts, data scientists, product owners, process experts and stakeholders to prioritize work, manage dependencies and deliver against the roadmap.
- Ensure technical documentation, requirements, design decisions, controls and support procedures are complete, current and endorsed by relevant stakeholders.
- Drive timely enrichment and optimization of data required for new regulations, control processes and Process and Transaction Monitoring solutions.
- Explore how data capabilities can support advanced analytics and future AI use cases, including responsible use of generative AI.
- Coach and mentor engineers, promote knowledge sharing and challenge the team to improve engineering practices, resilience and delivery discipline.
- Contribute actively to Agile ceremonies and foster transparent planning, early escalation and fact-based decision-making.
- You are not only expected to build solutions, but also to shape how designs, governs and operates its data engineering capabilities.
- BI experience in Power BI, Cognos, Tableau, Looker is preferable
- Act as the primary bridge between business teams, Change, BAU, Architecture and BIDS, ensuring data capabilities are aligned with strategic business priorities and operational needs.
- Drive the integration of data capabilities across by promoting shared standards, reusable solutions, cross-functional collaboration and early involvement of data expertise in strategic initiatives.
- Represent Data in cross-domain forums, architecture discussions and strategic initiatives across Wholesale Banking.
Technical skills we are looking for:
- At least 8 years of relevant experience in data engineering, cloud engineering, data analytics or a closely related technical field.
- Proven hands-on experience designing and building complex production-grade data pipelines using ETL and ETL patterns.
- Strong programming skills in Python and SQL, with practical experience using PySpark for distributed data processing.
- Hands-on experience with Apache Spark and workflow orchestration tools such as Apache Airflow.
- Experience with cloud data platforms, preferably Google Cloud Platform and BigQuery, and working knowledge of Azure or AWS.
- Strong understanding of data modelling, normalization and denormalization, data integration, data lakes and data warehouses.
- Experience with relational and non-relational data stores, including technologies such as MS SQL, Hive and dbt, plus object storage such as Amazon S3.
- Experience with containerization, orchestration and automated delivery tooling, including Docker, Kubernetes and CI/CD pipelines.
- Experience managing and optimizing distributed systems and clusters for large-scale batch processing.
- Good command of software engineering practices, including modular design, testing, code review, documentation, security and production support.
Soft skills we are looking for:
- Curious mindset; you are collaborative and passionate about helping others to grow and improve,
- Proactive, hands on - can-do mentality, on top of your delivery (no surprises) and positive mind-set
- The ability to facilitate decision-making to drive complex design issues to a conclusion. - Team player with good communication skills (Fluent in English) and experienced in working in an international environment.
- Strong organisational sensitivity: ability to understand and consider the underlying issues, opportunities and dynamics of an international organisation with multiple functional and hierarchical lines, dealing with multiple (sometimes conflicting) interests.
- A strong resilience: the ability to navigate through ambiguity and simplify complexity without losing essence.
- Excellent communication skills, including being able to explain technical terms to non technical audience Competencies and experience:
- Minimum of 8 years working experience in the technical data or cloud role - At least 8 years of proven track record in delivering Data, BI or IT solutions, preferably with an Agile Way of Working
- Strong understanding of the main building blocks of data pipelines, ETL/ELT processes, and managing data lakes and warehouses
- Experience in data modeling, normalization/denormalization, and integrating data across complex systems
- Prior experience in Python, SQL, PySpark, dbt Labs for data processing and automation. - Good to have: Understanding of Financial Markets and Group Treasury business, FM/GT related products, KYC, FM regulations (EMIR, MIFID, SFTR, AFSL, MAS etc) and financial institutions (brokers, CCP’s, venues etc.)