Senior Software Engineering Manager - Front Office Data & Analytics
Posted on Sep 6, 2019 by McCabe & Barton
My client, a leading global asset manager based in the City of London, are hiring a Senior Software Engineering Manager to lead their Analytics and Data Engineering team in building a suite of next-generation n-tier, native cloud enabled applications. In this role, you will lead a global team of 10-12 engineer and data analysts to support the Analytics platform and develop new capabilities using modern web/cloud technologies used by our Portfolio Managers and Quantitative Analysts.
- High achiever who combines ambition with humility and is happy to let their performance do the talking.
- The ideal candidate will have strong collaboration skills as well as possess a passion for technology and staying sharp in your craft by keeping on top of new technologies, tools and trends
- Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
- Focused on delivering value to the business with relentless efforts to improve process
Leadership and management:
- Maintain high standards, develop others and match people to job design
- Design of effective engineering processes
- Product development expertise
- Architecture, craftsmanship & engineering discipline
Domain skills & experience
- A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review or pairing, unit testing, refactoring and related approaches.
- Excellent problem-solving and critical-thinking skills; demonstrated ability to employ fact-based decision-making to resolve complex problems, by applying logic analysis, experience and business knowledge
- Proven ability to quickly earn the trust of sponsors and key stakeholders; mobilize and motivate teams; set direction and approach; resolve conflict; deliver tough messages with grace; execute with limited information and ambiguity
- Ensure a portfolio of excellent & enduring products and processes that fulfil the customer need
- Ensure the application designs and engineering processes fulfil the target operating model and architecture with maximum agility and efficiency
- Enable excellent teamwork
- Manage great engineering talent
- Ensure excellent customers relationships
- Ensure product delivery is of a high quality with each release
- Mentor, coach, and develop a high performing engineering team, using a servant leadership style
- Conducting release planning, sprint planning, product and sprint backlog grooming, sprint reviews, retrospectives, daily standup meetings, user story development, estimation, and other related activities
- Assessing the Agile Maturity of the team and organization and coaching the team to higher levels of maturity, at a pace that is sustainable
- Work closely with architecture team to organize and participate in architecture reviews, develop practices and ensure standards and roadmaps are adhered to
Technology and Business Skills:
- Expert knowledge in one or more programming language(s) - Python, Java, C/C++
- Proficient with a range of open source frameworks and development tools Angular/Backbone/ReactJS, Esper, Python (NumPy, SciPy, pandas), Pyramid, etc.
- Experience building modern web applications and deploying to public or private clouds, such as Amazon Web Services (AWS), Microsoft Azure, or similar providers.
- Proficient on Linux platforms with knowledge of various Scripting languages
- Strong knowledge of one or more relevant database technologies eg Oracle, MongoDB, Hadoop, KDB/OneTick
- Familiarity with a variety of programming styles (eg OO, functional) and in-depth knowledge of design patterns
- Strong Test-Driven Development and desire to write simple, adaptive and iterative code.
Strong preference for:
- A solid understanding of tradable financial instruments (securities, derivatives) and capital markets
- Experience of web-based development and visualisation technology for portraying large and complex data sets and relationships
- An advanced level of relevant mathematical knowledge eg statistics, time-series analysis, asset pricing theory, optimisation algorithms.
- Experience with algorithms and data structures
- Strong academic record and a degree with high mathematical and computing content eg Computer Science, Mathematics, Engineering or Physics from a leading university.