Senior Data Developer/Data Engineers

MANDATORY REQUIREMENT(S) 3 Years of experience in collaborating with the client’s teams and data and system analysts to understand their data requirements and translate them into scalable and robust data solutions, design data models, data pipelines, and integration processes to acquire, transform, and store investment-related data from various sources, as well as, have a strong understanding of relational and non-relational databases, data modeling, and query optimization.7 years of experience in developing ETL processes, data engineering, database development and data integration workflows to gather and combine data from different sources such as market data providers, trading platforms, and internal systems. Perform data analysis, data validation, and data cleansing to ensure data accuracy and integrity.3 years of experience in design and optimize database structures, relational and dimensional data modelling, data design and schemas specifically tailored for investment data storage and retrieval, as well as excellent understanding of modern big data technologies including data lakes and data warehouses with knowledge of the underlying architecture5 years of experience in Python and SQL programming languages.3 years of experience in the following technology stack: Azure Data Lake, Azure Data Factory, Databricks, (and DBT –Optional).2 years of experience with agile software development experience including the use of DevOps tools such as JIRA and Azure DevOps (ADO). REQUIRED (Attributes) 2 years of experience to collaborate with data analysts and investment professionals to identify and implement investment analytics models, algorithms, and techniques, develop data pipelines and workflows to support portfolio analysis, risk assessment, performance attribution, and other investment-related analytics tasks, have in-depth knowledge of investment data sources, such as market data feeds, trading platforms, and financial databases.Familiarity with investment analytics concepts, including portfolio analysis, risk assessment, and performance attribution will warrant additional points.2 years of experience to collaborate with cross-functional teams to establish data quality standards specific to investment data, and development, data validation, data cleansing, data management and data enrichment processes to maintain high-quality investment data as well as knowledge of investment regulations, compliance requirements, and data privacy regulations in the investment industry.3 years of experience with investment analytics concepts, including portfolio analysis, risk assessment, and performance attribution.

Key Skills

• Python
• SQL