About Clearwater Analytics: 

Clearwater Analytics, global industry-leading SaaS solution, automates the entire investment lifecycle. With a single instance, multi-tenant architecture, Clearwater offers award-winning investment portfolio planning, performance reporting, data aggregation, reconciliation, accounting, compliance, risk, and order management. Each day, leading insurers, asset managers, corporations, and governments use Clearwater’s trusted data to drive efficient, scalable investing on more than $6.4 trillion in assets spanning traditional and alternative asset types. 

Our mission: To be the world’s most trusted and comprehensive technology platform that simplifies the entire investment lifecycle and eventually revolutionizes the world of investing. 

Job Summary:  

As a hands-on Data Engineer at Clearwater Analytics (CWAN), you will turn business and platform data into actionable insights that drive decision making. You will use Python and SQL to extract, clean, and analyze data, and contribute to building the data pipelines that feed your dashboards and analysis. You will build dashboards and reports, analyze key business and platform performance metrics, and work closely with cross functional teams to understand their data and reporting needs.

Responsibilities and Duties

• Analyze business and platform performance metrics to surface trends, risks, and opportunities for stakeholders

• Contribute to building and maintaining data pipelines that feed dashboards, reports, and analytical tools

• Write Python and SQL to extract, clean, transform, and analyze data from various sources

• Build and maintain BI dashboards and reports (e.g., Power BI, Tableau) that make data and business metrics easy to understand and act on

• Partner with Business Analysts, Product Owners, and other cross functional teams to gather requirements and translate them into meaningful analysis and reporting

• Support the wider business with ad hoc data and reporting requests

• Identify data quality issues and partner with engineering teams to help resolve them

• Document metrics definitions, data sources, and reporting logic to ensure consistency and clarity across teams

• Continually look for opportunities to improve analytical workflows and reporting processes

Required Skills

• Strong hands on proficiency in Python for data processing, analysis, and automation is required

• Proficiency in SQL and deep knowledge of various data platforms (e.g. Snowflake, Databricks, Redshift)

• Solid understanding of business and platform related metrics, with the ability to translate data into clear, actionable insights

• Experience building dashboards and reports using BI/data visualization tools (e.g., Power BI, Tableau)

• Experience building or contributing to data pipelines that support analytics and reporting

• Strong analytical and problem solving skills

• Familiarity with data governance principles and data quality best practices

• Experience in the finance industry will be a significant advantage

• Experience utilizing ETL tools and technologies such as DBT, Fivetran, ADF, SSIS is a good to have

• Exposure to GenAI/LLM technologies (e.g., prompt engineering, LLM-based data processing, RAG pipelines) is a good to have

Education and Experience

• Degree in Computer Science, Data Analytics, Statistics, or a related field

• 3 - 7 years of hands-on experience in data analysis, reporting, or business intelligence, with a track record of turning data into business insights