Financial/Investment Data Engineer (SQL queries/ETL/DWH)
Summary
Build and optimize Snowflake-based data pipelines and ETL workflows, then write complex SQL to transform financial data for reporting and analysis.
Responsibilities
Data Infrastructure Development:
- 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 Description: Education: - 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 model 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.
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 Description: Education: - 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 model 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.