Lead Data Engineer With Databricks Python And Investment- Remote

Lead Data Engineer - Remote Must have the following: Databricks Python ETL Experience working in the Investment Management industry.

An overview is below but the above are requirements: Responsibilities of the position: Investment Data Solution Design:

Collaborate with investment teams and data 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. Investment Data Integration and Analysis:

Develop ETL processes 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. Develop tools and frameworks for data visualization and reporting to support investment analysis and decision-making.

Database Management: Design and optimize database structures and schemas specifically tailored for investment data storage and retrieval. Ensure efficient data indexing, partitioning, and query optimization techniques are implemented to support fast and accurate data retrieval.

Monitor database performance and make recommendations for improvements. Investment Analytics: 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. Data Quality and Governance: Collaborate with cross-functional teams to establish data quality standards and data governance policies specific to investment data.

Implement data validation, data cleansing, and data enrichment processes to maintain high-quality investment data. Ensure compliance with regulatory requirements and industry best practices related to investment data management and privacy. Years of experience in industry or field Solid experience (5 years) in data engineering, database development, or a similar role, preferably within the investment industry.

Strong proficiency in programming languages like Python, SQL, and R. Hands on experience in the following technology stack: Azure Data Lake, Azure Data Factory, Databricks, and DBT is a plus Excellent understanding of modern big data technologies including data lakes and data warehouses with knowledge of the underlying architecture 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. Experience with ETL tools, data integration platforms, and data visualization tools. Proven experience of working with cloud-based system Strong understanding of relational and non-relational databases, data modeling, and query optimization.

Knowledge of investment regulations, compliance requirements, and data privacy regulations in the investment industry. Estimated Min Rate : $63.00 Estimated Max Rate : $90.00 Note: Any pay ranges displayed are estimations.

Actual pay is determined by an applicant's experience, technical expertise, and other qualifications as listed in the job description. All qualified applicants are welcome to apply. Yoh, a Day & Zimmermann company, is an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Visit https://www.yoh.com/applicants-with-disabilities to contact us if you are an individual with a disability and require accommodation in the application process.