Data Engineer – EU

Axxsys is part of the Alpha Financial Markets Consulting (Alpha FMC) group, the leading global consultancy to the asset and wealth management industry. We are a boutique management consulting firm that offers the world’s top asset and wealth managers a competitive edge through our expertise and industry insight.

Our team is of a uniquely high calibre and by focusing on asset and wealth management alone we build deep knowledge and experience within our industry. We work with a blue-chip client base, including 21 of the top 25 largest global asset management firms, and work with over 130 clients across the globe. We have our headquarters located the United Kingdom, as well as offices in major global financial centres across the United States, Canada, France, Luxembourg, Switzerland, Denmark and Asia.

Axxsys

Axxsys is a division of the Alpha Group, which provides high quality Financial Management and Technology consultancy to the global buy-side sector.

We are experts in providing business and technical integration services to a range of high-profile clients on a variety of large, high value change programmes. We specialize in configuring and integrating system and data components to optimise workflows and business intelligence for Investment Management companies.

To date, Axxsys has partnered with 50+ clients globally, ensuring they achieve the maximum return on their investment in software systems, optimize processes, and remain at the forefront of technology trends within the investment management market. Axxsys provides services across a number of areas including Project Planning, Scoping, Business Requirements, Target Process Modelling, Project Management, Implementation, Integration, Test Management and Target Operating Model (TOM).

Axxsys, and the Alpha Group more widely, pride ourselves in being a meritocratic environment perfect for building a career, meeting great people, as well as a rewarding place to work.

The Role

Axxsys is looking for Data Engineers to join our growing team. We are looking for individuals with subject matter expertise in Data Modelling, Business Intelligence and Data Management. You will be part of a highly collaborative and growing team of technology and data experts, who are taking on today’s most complex challenges in Asset and Wealth Management industry.

You will –

  • Build data pipelines and applications to stream and process financial datasets
  • Lead data modelling activities to capture and model data requirements, business rules, and logical and physical models
  • Design, code, and tune ETL pipelines using Talend, Informatica or similar technologies
  • Data profiling and source-to-target mapping (including complex business rules)
  • Create a value chain to help address the challenges of acquiring data, evaluating its value, distilling, and analysing

Skill Requirements

  • 5+ years of experience in data analysis, engineering, architecture, roles, including experience with transformational efforts
  • Knowledge of data warehousing concepts
  • Experience in data mining, profiling, and analysis
  • Experience with complex data modelling, ETL design, and using large databases in a business environment
  • Proficiency with Linux command line and systems administration
  • Experience with languages like Python, Ruby, Java, or similar language
  • Understanding of Big Data technologies such as Hive/Spark

 Other Skills

  • Excellent interpersonal and client relationship skills
  • Entrepreneurial approach
  • Proven experience in building and delivering solutions in Financial Services
  • Outstanding demonstrated verbal and written communication

We are committed to employing individuals from all backgrounds, that reflects the multi-cultural society we live in. We pride ourselves on operating an inclusive working environment and providing the best people to meet our client’s expectations of service. We would like to hear from you if you are motivated, take pride in the value you add to your clients and keen to join a team of like-minded individuals.

Apply here