Data Engineering Lead
London, London, United Kingdom
InvestCloud
InvestCloud powers digital transformation in financial services. Scale your business with digital wealth management and APL network access today.Key Responsibilities
- Implement, manage and maintain data platforms such as Oracle, Snowflake, and/or Databricks, ensuring high availability and performance, whilst optimizing for cost.
- Assist in the Design, development, and maintenance of scalable data pipelines to support diverse analytics and machine learning needs.
- Optimize and manage data architectures for reliability, scalability, and performance.
- Implement and support data integration solutions from our data partners, including ETL/ELT processes, ensuring seamless data flow across platforms.
- Collaborate with Data Scientists, Analysts, and Product Teams to define and support data requirements.
- Ensure data security and compliance with company policies and relevant regulations.
- Monitor and troubleshoot data systems to identify and resolve performance issues.
- Develop and maintain datasets and data pipelines to support Machine Learning model training and deployment
- Analyze large datasets to identify patterns, trends, and insights that can inform business decisions.
- Work with 3rd party providers of Data and Data Platform products to evaluate and implement solutions achieving Investcloud’s business objectives.
Required Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Minimum of 5 years of professional experience in data engineering or a related role.
- Proficiency in database technologies, including Oracle and PostgreSQL.
- Hands-on experience with Snowflake and/or Databricks, with a solid understanding of their ecosystems.
- Expertise in programming languages such as Python or SQL.
- Familiarity with ETL/ELT tools and data integration frameworks.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with containerization and CI/CD tools (e.g., Docker, Git).
- Excellent problem-solving skills and the ability to handle complex datasets.
- Outstanding communication skills to collaborate with technical and non-technical stakeholders globally.
- Knowledge of data preprocessing, feature engineering, and model evaluation metrics
- Excellent proficiency in English
- Ability to work in a fast-paced environment across multiple projects simultaneously
- Ability to collaborate effectively as a team player, fostering a culture of open communication and mutual respect.
Preferred skills
- Knowledge of data warehousing and data lake architectures.
- Familiarity with governance frameworks for data management and security.
- Knowledge of Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn) and LLM frameworks (e.g. Langchain)
What do we offer
Join our diverse and international cross-functional team, comprising data scientists, product managers, business analyst and software engineers. As a key member of our team, you will have the opportunity to implement cutting-edge technology to create a next-generation advisor and client experience.
Location and Travel
The ideal candidate will be expected to work from the London office (with some flexibility). Occasional travel may be required.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure CI/CD Computer Science Databricks Data management Data pipelines Data Warehousing Docker ELT Engineering ETL Feature engineering GCP Git LangChain LLMs Machine Learning Model training Oracle Pipelines PostgreSQL Python PyTorch Scikit-learn Security Snowflake SQL TensorFlow
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