Sr. Technical Data Analyst

Clearwater Analytics

About The Position

The Technical Data Analyst is responsible for maintaining investment data for clients. The role includes analyzing and organizing raw data, building data systems and pipelines, conducting complex data analysis, and presenting information through data visualization. The analyst collaborates with clients and project management teams to understand customer and company needs, combines data from various sources to meet those needs, and works to improve data quality and reliability. The role also contributes to creating, implementing, and maintaining investment data for Clearwater's clients.

Requirements

Deep understanding of investment data.
Familiarity with cloud platforms and big data technologies such as AWS, GCP, or Azure.
Understanding of database design and data warehouse principles.
Knowledge of one or more programming languages, such as Java, Python, or VBA.
Proficiency in data manipulation and data cleansing techniques.
Knowledge of data governance and data management best practices.
Continuous improvement mindset for self and team.
Ability to collaborate in a cross-functional team environment.
Ability to work with large datasets and perform data mining.
Strong computer skills, including proficiency in Microsoft Office.
Excellent attention to detail and documentation skills.
Outstanding verbal and written communication skills.
Strong organizational and interpersonal skills.
Exceptional problem-solving abilities.
Bachelor’s degree in data analytics, statistics, accounting, computer science, or a related discipline.
7+ years of relevant experience in data analytics, reporting, and visualization.
Hands-on experience with SQL and NoSQL databases.
Experience with data integration, exchange, transfer, and load processes.
Experience with data visualization tools such as Tableau, Power BI, or D3.js.

Responsibilities

Analyze and organize raw data to produce useful insights.
Build efficient and robust data systems and pipelines.
Analyze complex datasets and report findings.
Present findings using data visualization techniques.
Combine information from multiple data sources into comprehensive, actionable insights.
Improve data quality and reliability.
Develop and implement analytical tools and programs to support data-driven decisions.
Collaborate with system architects and product development teams.
Work directly with clients and project management teams to understand customer and company needs.
Create, implement, and maintain investment data for clients.