Eleven Recruiting
About Eleven Recruiting
We are a specialized technology staffing agency supporting professional and financial services companies. Why do we stand out in technology staffing? We listen and act as advisors for our candidates on how they can best add value, find interesting projects, and pave a path for career advancement. We advocate for best pay, diversity in tech, and best job-fit for every candidate we place.
Our client, an investment firm, is seeking a VP, Senior Data Engineer to join their team in Los Angeles, CA!
Responsibilities:
Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services. Develop code using ETL and ELT processes to transform data from Bronze to Silver, and Gold layer of maturity of data. Ensure DevOps for code development and deployment. Perform Unit testing, system testing, QA testing and integrated engineering; Automated testing. Managing and optimizing data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Synopse, Microsoft Fabric. Developing data models and maintaining data architecture to support data analytics and business intelligence reporting. Ensuring data quality and consistency through data cleaning, transformation, and integration processes. Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services. Technical Responsibilities:
Develop and maintain robust data pipelines using Azure Data Factory, orchestrating the flow of data from various sources, including Bloomberg, FactSet, Morningstar, and internal systems. Utilize Azure Databricks (or similar Azure tech stack) to perform data transformations, cleansing, and aggregations, preparing data for analysis and reporting purposes. Implement data quality checks and validation rules to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle. Develop and maintain data models for investment data, ensuring alignment with business requirements and supporting efficient data analysis and reporting. Optimize data storage and retrieval processes using Azure Data Lake Storage, Azure SQL Database, and Azure Cosmos DB, Azure Synopse, or Azure Fabric selecting the most appropriate storage solutions based on data characteristics and performance needs. Collaborate with data scientists and business analysts to understand data requirements and implement data solutions that meet those needs effectively. Contribute to the development and maintenance of documentation related to data pipelines, data models, and data quality processes.
Qualifications:
Bachelor's degree in Computer Science, Finance, or other relevant discipline. 10+ years of experience in data and analytics space and 8+ years of experience in job specific work. Knowledge of the asset management industry and asset classes to bridge business and technology for data solutions. Strong understanding of key data concepts (e.g., Portfolio Construction, Security/Account Reference data, AUM, Investment Results/Attribution, Index/Benchmark). Experience with industry data (e.g., Bloomberg, FactSet, Morningstar, ESG, Index, alternative data). Hands-on experience with data warehouse, data lake, and cloud solutions, collaborating with data engineering teams.
Personal Attributes:
Relationship Building: works effectively with strong, diverse teams of people with multiple perspectives, talents, and backgrounds. He or she is known for doing what is best irrespective of politics and is comfortable with consensus building (at multiple levels) and soliciting constructive feedback; ability to elicit cooperation from a wide variety of participants including upper management, clients, other departments, and 3rd party providers. Communication: strong interpersonal and verbal/written communication skills; ability to present complex material. Independence & Collaboration: experience at working both independently and in a team-oriented, collaborative environment; must be able to drive work effectively with limited supervision (at times) while representing department and executive management interests and concerns. Work Ethic: focus on continual development, performance, accountability, and self-motivation. Flexibility & Organization: adapt to shifting priorities, demands and timelines through analytical and problem-solving capabilities; proven ability to multi-task and efficiently manage time across competing activities/resources; able to effectively prioritize, execute tasks, and thrive in a high-pressure fast paced environment. Intellectual Curiosity: energized by learning new things and engaging across a wide range of issues; must have strong problem solving skills; understand the importance of attention to detail, adept at conducting research into project-related issues and products; displays a technical aptitude that lends itself to learning and mastering new technologies. Driving Results: sets aggressive timelines and objectives to drive results, conveys a sense of urgency, and drives issues to closure; is a self-starter committed to achieving results and has a strong sense of ownership and follow-through. Judgment: makes recommendations and decisions that balance a variety of factors.
Our client, an investment firm, is seeking a VP, Senior Data Engineer to join their team in Los Angeles, CA!
Responsibilities:
Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services. Develop code using ETL and ELT processes to transform data from Bronze to Silver, and Gold layer of maturity of data. Ensure DevOps for code development and deployment. Perform Unit testing, system testing, QA testing and integrated engineering; Automated testing. Managing and optimizing data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Synopse, Microsoft Fabric. Developing data models and maintaining data architecture to support data analytics and business intelligence reporting. Ensuring data quality and consistency through data cleaning, transformation, and integration processes. Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services. Technical Responsibilities:
Develop and maintain robust data pipelines using Azure Data Factory, orchestrating the flow of data from various sources, including Bloomberg, FactSet, Morningstar, and internal systems. Utilize Azure Databricks (or similar Azure tech stack) to perform data transformations, cleansing, and aggregations, preparing data for analysis and reporting purposes. Implement data quality checks and validation rules to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle. Develop and maintain data models for investment data, ensuring alignment with business requirements and supporting efficient data analysis and reporting. Optimize data storage and retrieval processes using Azure Data Lake Storage, Azure SQL Database, and Azure Cosmos DB, Azure Synopse, or Azure Fabric selecting the most appropriate storage solutions based on data characteristics and performance needs. Collaborate with data scientists and business analysts to understand data requirements and implement data solutions that meet those needs effectively. Contribute to the development and maintenance of documentation related to data pipelines, data models, and data quality processes.
Qualifications:
Bachelor's degree in Computer Science, Finance, or other relevant discipline. 10+ years of experience in data and analytics space and 8+ years of experience in job specific work. Knowledge of the asset management industry and asset classes to bridge business and technology for data solutions. Strong understanding of key data concepts (e.g., Portfolio Construction, Security/Account Reference data, AUM, Investment Results/Attribution, Index/Benchmark). Experience with industry data (e.g., Bloomberg, FactSet, Morningstar, ESG, Index, alternative data). Hands-on experience with data warehouse, data lake, and cloud solutions, collaborating with data engineering teams.
Personal Attributes:
Relationship Building: works effectively with strong, diverse teams of people with multiple perspectives, talents, and backgrounds. He or she is known for doing what is best irrespective of politics and is comfortable with consensus building (at multiple levels) and soliciting constructive feedback; ability to elicit cooperation from a wide variety of participants including upper management, clients, other departments, and 3rd party providers. Communication: strong interpersonal and verbal/written communication skills; ability to present complex material. Independence & Collaboration: experience at working both independently and in a team-oriented, collaborative environment; must be able to drive work effectively with limited supervision (at times) while representing department and executive management interests and concerns. Work Ethic: focus on continual development, performance, accountability, and self-motivation. Flexibility & Organization: adapt to shifting priorities, demands and timelines through analytical and problem-solving capabilities; proven ability to multi-task and efficiently manage time across competing activities/resources; able to effectively prioritize, execute tasks, and thrive in a high-pressure fast paced environment. Intellectual Curiosity: energized by learning new things and engaging across a wide range of issues; must have strong problem solving skills; understand the importance of attention to detail, adept at conducting research into project-related issues and products; displays a technical aptitude that lends itself to learning and mastering new technologies. Driving Results: sets aggressive timelines and objectives to drive results, conveys a sense of urgency, and drives issues to closure; is a self-starter committed to achieving results and has a strong sense of ownership and follow-through. Judgment: makes recommendations and decisions that balance a variety of factors.