Data Engineer

About the Team

You will be joining the newly formed AI, Data & Analytics team, primarily responsible as a Data Engineer leading various projects within the new Data Platform team. The new team is focused on driving increased value from the data InvestCloud captures to enable a smarter financial future for our clients, in particular focused on “enhanced intelligence”. Ensuring we have fit-for-purpose modern capabilities is a key goal for the team.

Key Responsibilities

• Assist in the Design, development, and maintenance of scalable data pipelines to support diverse analytics and machine learning needs.

• Manage data architectures for reliability, scalability, and performance.

• 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.

• Manage and maintain data platforms such as Oracle, Snowflake, and/or Databricks, ensuring high availability and performance, whilst optimizing for cost.

• 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 4 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.

• Experience with 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).

• Strong problem-solving skills and the ability to handle complex datasets.

• Good communication skills to collaborate with global technical and non-technical stakeholders.

• 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.

• Familiarity with Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn) and LLM frameworks (e.g. Langchain)