Data Engineer Asset Management London, Hybrid

Job Purpose

As a Data Engineer, you'll be at the forefront of enhancing our client's data capabilities, ensuring every bit is optimised for success. You will be collaborating closely with their visionary Data Scientists, crafting intricate data models and stunning visualisations that will drive strategic decision-making to new heights. Your expertise in programming languages and data analysis tools will be the key to unlocking their data's full potential. Your contributions will be pivotal in driving strategic decision-making, fueling various impactful use cases. Harness your prowess in programming languages and data analysis tools, while showcasing your formidable analytical and communication skills.

Responsibilities

• Support the design and maintenance of data integrity checks across our client's various systems.
• Collaborate with the Data Scientists to understand data needs, representing key data insights in a meaningful way.
• Building data pipelines to bring together information from different source systems that will integrate, consolidate, and cleanse data and structure it for use in analytics applications.
• Collaborate with Developers to design and implement scalable data pipelines for efficient data processing and analysis.
• Conduct exploratory data analysis to identify patterns, trends, and anomalies in financial data, and provide recommendations for actionable insights to the Data Scientist.
• Focus on collecting and preparing data for use by Data Scientists and analysts.
• Solve challenging data integration problems, utilising optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources.
• Support the design, build, and launch collections of sophisticated data models and visualisations that support multiple use cases across different products or domains.
• Optimise dashboards, frameworks, and systems to facilitate easier development of data artifacts.
• Undertake technical or any other relevant training as and when required.
• Be proactive in developing your knowledge of the industry and the market. Undertake and record relevant Continuous Professional Development (CPD) to develop knowledge and skills.

Competencies

Technical /Qualifications

• Degree, ideally in computer science, IT, statistics, analytics, mathematics or other related field.
• Proven experience in data engineering, data analysis/ processing, machine learning techniques, data warehouses, data pipelines, preferably in a Financial Services or Wealth Management environment.

Systems/Internal Processes

• Familiarity with programming languages such as Python, R or Java and with data analysis libraries (e.g. Pandas, NumPy, scikit-learn).
• Understanding of database technologies (ETL) and SQL proficiency for data manipulation, data mining and querying.
• Knowledge of Big Data Tools (Spark or Hadoop a plus).
• Power BI, Dashboard design / development.

Regulatory Awareness/Compliance

Uphold Regulatory/Compliance requirements relevant to your role escalating areas of concern or issue in a timely manner.

Core Competencies/Skills

• Excellent analytical, statistical, and problem-solving capabilities
• Ability to work independently and proactively
• Ability to analyse large amounts of data and make deductions and decisions from the data which will add to the growth of the business.
• Strong vision to develop enhancements to systems
• Excellent communication skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders
• Highly motivated and adaptable, with a passion for leveraging data-driven insights to solve business challenges and drive strategic decision-making

Morgan McKinley is acting as an Employment Agency and references to pay rates are indicative.

BY APPLYING FOR THIS ROLE YOU ARE AGREEING TO OUR TERMS OF SERVICE WHICH TOGETHER WITH OUR PRIVACY STATEMENT GOVERN YOUR USE OF MORGAN MCKINLEY SERVICES.