Product Analyst

Omm IT Solutions

9d•Onsite

About The Position

Analyze product and business data to generate actionable insights that drive decision-making and product improvements. Write complex queries across SQL and NoSQL (MongoDB) data sources to extract, transform, and analyze large, distributed datasets. Partner closely with Product Owners to translate analysis into well-defined user stories, support backlog grooming, and contribute to sprint planning. Collaborate with product managers, engineering, and business stakeholders to convert business needs into clear, data-driven requirements for development teams. Support and validate ETL processes by working with data engineers to ensure data quality, integrity, and optimized data flows. Develop and maintain dashboards, reports, and KPIs to monitor product health and user behavior. Conduct deep-dive analysis and root cause investigations across product performance, user journeys, and operational issues. Work with QA and engineering teams to validate data accuracy and support end-to-end testing. Contribute to continuous improvement by identifying data gaps, inefficiencies, and automation opportunities. Operate effectively within event-driven architectures, understanding how data flows across systems and impacts downstream analytics.

Requirements

8+ years of experience as a Product/Data Analyst.
Strong expertise in SQL and working knowledge of NoSQL databases (e.g., MongoDB).
Proven ability to translate analytical findings into actionable product requirements and user stories.
Hands-on experience supporting backlog grooming, sprint planning, and Product Owner collaboration.
Experience in the mortgage industry (Freddie Mac / Fannie Mae exposure is a strong plus).
Solid understanding of data modeling, data analysis, and working with large-scale data warehouse environments.
Experience with ETL processes and data validation (Informatica or similar tools preferred).
Familiarity with event-driven architecture and data flow patterns across distributed systems.
Strong analytical and problem-solving skills with the ability to influence business decisions.
Experience working in Agile/Scrum environments, with tools such as Jira.
Excellent communication skills, with the ability to clearly articulate insights and requirements to both technical and non-technical stakeholders.

Nice To Haves

Freddie Mac / Fannie Mae exposure

Responsibilities

Analyze product and business data to generate actionable insights that drive decision-making and product improvements.
Write complex queries across SQL and NoSQL (MongoDB) data sources to extract, transform, and analyze large, distributed datasets.
Partner closely with Product Owners to translate analysis into well-defined user stories, support backlog grooming, and contribute to sprint planning.
Collaborate with product managers, engineering, and business stakeholders to convert business needs into clear, data-driven requirements for development teams.
Support and validate ETL processes by working with data engineers to ensure data quality, integrity, and optimized data flows.
Develop and maintain dashboards, reports, and KPIs to monitor product health and user behavior.
Conduct deep-dive analysis and root cause investigations across product performance, user journeys, and operational issues.
Work with QA and engineering teams to validate data accuracy and support end-to-end testing.
Contribute to continuous improvement by identifying data gaps, inefficiencies, and automation opportunities.
Operate effectively within event-driven architectures, understanding how data flows across systems and impacts downstream analytics.