Data Engineer

About InvestCloud

• 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 Investclouds business objectives.

Required Skills

• Bachelors or Masters 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