Key Skills

Job Description

Create your own future As a Data Engineer within Investment Management Technology & Analytics (IMTA), you will help build and evolve the data and analytics platform used by investment professionals across Van Lanschot Kempen. You will work in a DevOps team responsible for investment and sustainability data and the solutions built on top of it. Our data supports a wide range of business-critical processes, including investment analysis, risk monitoring, regulatory and client reporting, and dashboards used to generate actionable insights. The team works closely with other IMTA DevOps teams focusing on analytics, dashboarding and AI. Together, we provide the data foundation, analytical capabilities and technology used by professionals in asset management, fiduciary management and manager selection. As a Data Engineer, you will design, build and continuously improve reliable data products and components of our investment data and analytics platform. You also have the following tasks: develop production-grade data pipelines and transformations using Python, SQL and PySpark; design data models that turn complex investment and sustainability data into well-structured, reusable datasets; build automated data-quality checks and engineering tests to ensure that our data is trustworthy; improve the reliability, performance, observability and maintainability of our data platform; contribute to engineering standards, architecture and technology choices within the team; use CI/CD and automated deployment practices to safely bring changes into production; collaborate directly with investment, risk and reporting specialists to translate business needs into robust technical solutions; help improve the team's software engineering practices and development processes; explore new technologies and opportunities in data engineering, analytics and AI where they can create business value. Our platform is built primarily on Microsoft Azure, using technologies including Azure Databricks, PySpark, Azure Data Factory, Azure Storage, Azure SQL and Git-based CI/CD. Your talents Curious, pragmatic and collaborative. This is how we can best describe you in the position of Data Engineer – Investment Management. Talents that you use to guide our customers in a constantly changing world every day. By thinking out of the box and asking questions. And all will be well if you enjoy solving complex data problems, take ownership from development through production, and care about creating solutions that remain understandable and reliable as they grow. You also have: have a bachelor's or master’s degree in computer science, Data Science, Mathematics, Engineering, Finance or a related field, or equivalent professional experience; have approximately five years or more relevant data engineering experience. Software engineering experience is nice to have; have strong programming skills in Python and SQL; are familiar with distributed data processing, for example using PySpark or an equivalent technology; understand data modelling and the principles of data quality and automated testing; have experience working with cloud-based data platforms. Experience with Azure and Databricks is particularly relevant; are comfortable working with Git, CI/CD and modern software-development practices; enjoy taking ownership of solutions from design and development through to production; enjoy collaborating with both engineers and business specialists; are curious, pragmatic and motivated to continuously improve both the technology and the way the team works. Experience with investment, financial or sustainability data is valuable, but not essential. More important is your ability and willingness to understand the business meaning behind the data you engineer. Move ahead at Van Lanschot Kempen Investing in line with our clients' beliefs and goals, supporting them in future-oriented, sustainable and data-driven decision-making. Both nationally and internationally. With nearly 300 years of experience, we make this ambition a reality at Van Lanschot Kempen. We do this with some 2,300 colleagues in various fields of expertise. Within IMTA, you will work in a highly collaborative environment where business and technology come together. We combine the dynamics of a start-up with the stability of an established organization, working on solutions that have real impact on our investment management capabilities. An organisation's degree of innovation and agility also depends on the diversity of its workforce. Our differences make us stronger together. We promote an inclusive work environment where all colleagues feel at home. With us, you can be yourself. And we are proud of that. Curious about the stories of colleagues and how they experience working at Van Lanschot Kempen? Go to Podcasts and find out more! That is what we do! The fact is, if you add value, you can expect the same from us in return. A good work-life balance with our ‘hybrid way of working’ is a good example of this. As a Data Engineer, you will also be given: You will also receive: A gross monthly salary between € 5.500 and € 7.000 depending on your knowledge and experience A flexible budget of 19.47% of your gross salary, including a 13th month and holiday allowance 27 leave days (with flexibility to adjust via the budget) Flexible working hours and hybrid working Training opportunities and the possibility to attend conferences An excellent pension scheme The possibility to work abroad for up to 2 months per year And we have many other employment benefits ready for you. Discover all the benefits of working at Van Lanschot Kempen. Excited about the vacancy? Please apply via our Career Website. Do you have any questions? Please get in touch with Anna Skorobohata, Recruiter, via [email protected]

Core Responsibilities

Design, build, and improve production-grade data pipelines, models, quality checks, and platform components for investment and sustainability data using Python, SQL, PySpark, and Azure technologies. Collaborate with investment, risk, and reporting specialists to deliver reliable data products, strengthen engineering practices, and support business-critical analytics and reporting.

Requirements

Candidates should have a bachelor's or master's degree in a relevant field or equivalent professional experience, approximately five or more years of relevant data engineering experience, and strong Python and SQL skills. They should understand distributed data processing, data modeling, data quality and testing, and cloud data platforms, with Azure and Databricks experience particularly relevant; investment, financial, or sustainability data experience is valuable but not essential.

Benefits

• Flexible Budget Including 13th-Month Salary and Holiday Allowance
• 27 Days of Leave
• Flexible Working Hours
• Hybrid Working
• Training Opportunities
• Conference Attendance
• Pension Scheme
• Option to Work Abroad for up to Two Months per Year