Modern Data Engineer

The Modern Data Engineer is responsible for designing, implementing, and maintaining scalable data architectures using cloud technologies, primarily on AWS, to support the next evolutionary stage of the Investment Process. They build robust data pipelines, optimize data storage, and access patterns, and ensure data quality while collaborating across engineering teams to deliver high-value data products

Key Responsibilities• Implement and maintain data pipelines for ingestion, transformation, and delivery• Ensure data quality through validation and monitoring processes• Collaborate with senior engineers to design scalable data solutions• Work with business analysts to understand and implement data requirements• Optimize data models and queries for performance and efficiency• Follow engineering best practices and contribute to team standards• Participate in code reviews and knowledge sharing activities• Implement data security controls and access policies• Troubleshoot and resolve data pipeline issues

Core Technical Skills

• Cloud Platforms:

  Proficient with cloud-based data platforms (Snowflake, data lakehouse architecture)

• AWS Ecosystem

  : Strong knowledge of AWS services including Lambda, Glue, and S3

• Streaming Architecture

  : Understanding of event-based or streaming data concepts using Kafka

• Programming:

  Strong proficiency in Python and SQL

• DevOps

  : Experience with CI/CD pipelines and infrastructure as code (Terraform)

• Data Security:

  Knowledge of implementing basic data access controls

• Database Systems

  : Experience with RDBMS (Oracle, Postgres, MSSQL) and exposure to NoSQL databases

• Data Integration

  : Understanding of data integration patterns and techniques

• Orchestration

  : Experience using workflow tools (Airflow, Control-M, etc.)

• Engineering Practices

  : Experience with GitHub, code verification, and validation

• Domain Knowledge:

  Basic knowledge of investment management industry concepts

Core Technical Skills

• Cloud Platforms:

  Proficient with cloud-based data platforms (Snowflake, data lakehouse architecture)

• AWS Ecosystem

  : Strong knowledge of AWS services including Lambda, Glue, and S3

• Streaming Architecture

  : Understanding of event-based or streaming data concepts using Kafka

• Programming:

  Strong proficiency in Python and SQL

• DevOps

  : Experience with CI/CD pipelines and infrastructure as code (Terraform)

• Data Security:

  Knowledge of implementing basic data access controls

• Database Systems

  : Experience with RDBMS (Oracle, Postgres, MSSQL) and exposure to NoSQL databases

• Data Integration

  : Understanding of data integration patterns and techniques

• Orchestration

  : Experience using workflow tools (Airflow, Control-M, etc.)

• Engineering Practices

  : Experience with GitHub, code verification, and validation

• Domain Knowledge:

  Basic knowledge of investment management industry concepts