Financial/Investment Data Engineer (SQL queries/ETL/DWH)

Responsibilities

• Design, implement, and maintain scalable and efficient data pipelines using Snowflake and SQL.

• Develop data models, ETL processes, and data integration workflows to ensure high data quality and reliability.

• Optimize data storage and retrieval performance in Snowflake.

Data Manipulation and Transformation

• Perform complex data manipulation and transformation using SQL to prepare data for analysis and reporting.

• Implement data cleansing, aggregation, and enrichment processes to ensure data accuracy and consistency.

• Develop and maintain reusable SQL scripts and stored procedures for data processing.

Collaboration and Support

• Collaborate with data analysts and other stakeholders to understand data requirements and deliver solutions that meet their needs.

• Provide technical guidance and mentorship to junior data engineers and other team members.

• Work closely with IT and DevOps teams to ensure seamless data integration and deployment.

Data Layer Preparation

• Design and build data layers to support various analytical and reporting needs.

• Ensure data layers are well‑documented, easily accessible, and performant.

• Implement data governance and security best practices to protect sensitive information.

Performance Tuning and Optimization

• Monitor and optimize the performance of data pipelines, databases, and queries.

• Identify and resolve performance bottlenecks to ensure timely and efficient data processing.

• Stay up‑to‑date with the latest trends and best practices in data engineering and apply them to improve our data infrastructure.

Mandatory Skills DescriptionEducation

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Experience

• Minimum of 2-5 years of experience in data engineering, with a strong focus on SQL and data manipulation.

• Proven experience working with Snowflake or other cloud‑based data warehousing solutions.

• Experience with Tableau.

• Strong background in designing data models and building scalable data pipelines and data models.

• Solid understanding of financial instruments, investment operations, investment reporting and portfolio management concepts.

• Knowledge of investment performance measurement, risk analysis, and portfolio management concepts.

Skills

• Expert‑level proficiency in SQL, with the ability to write complex queries and optimize them for performance.

• Strong experience with ETL tools and processes.

• Familiarity with Tableau.

• Knowledge of data governance, security, and compliance best practices.

• Excellent problem‑solving and analytical skills.

• Strong communication and collaboration skills.