Description
Data Analyst – Business Insights
New York, New York, United States
This organization is a global communications solutions provider offering a comprehensive suite of fully managed services focused on secure connectivity, networking, and mobility . It supports businesses and government agencies by simplifying communications and network operations . Clients include many Fortune 500 companies, and the organization is recognized as an industry leader . With a broad technology portfolio, integrated partnerships, and a private network, it delivers tailored solutions across design, deployment, and ongoing management — driving efficiency, innovation, and enabling customers to focus on core objectives .
The team values each member’s contribution to long‑term success and provides an environment where professionals can grow, collaborate, share knowledge, and build a rewarding career .
Role Overview
As a Data Analyst, you will develop metrics that provide consistent visibility and actionable insights for stakeholders. You will learn to distinguish between operational reporting that requires immediate action and strategic reporting that shapes long‑term initiatives, and you will build each type accordingly. You will work directly with AI‑powered engineering tools as part of your daily workflow, using them to generate and validate code while applying your own judgment to ensure architectural quality. This is a full‑stack analytics role involving SQL, data lineage, and front‑end dashboard development .
Role and Responsibilities
KPI Definition & Governance
Translate business questions into precise metric definitions, documenting grain, time basis, and exclusion rules. Maintain consistency so metrics like “Billed Revenue” or “Overdue Task” have a single definition across the organization .
Operational & Strategic Reporting
Build reporting for both immediate operational needs and long‑term strategic decision‑making, understanding how cadence, grain, and framing differ between the two .
Business Partnership
Collaborate closely with supported teams to understand their responsibilities, decision‑making processes, and blind spots. Push back when requested metrics are vanity measures or misaligned with desired behaviors .
Reporting Ownership
Own the end‑to‑end reporting layer for assigned business units, becoming the go‑to person who can explain why a number appears as it does .
SQL Development & Data Lineage
Write and optimize SQL queries against the data warehouse, ensuring clear traceability from dashboard figures back to source systems. You should be able to trace any number back to the exact row it originated from .
Dashboard Development & Maintenance
Maintain existing dashboards for accuracy and performance. Build new pages in the internal React application, including writing queries, wiring APIs, and implementing front‑end views .
AI‑Augmented Development
Use AI coding tools to generate and refactor code, applying careful review and validation before production deployment .
Ad Hoc Analysis & Communication
Respond to one‑off business questions, present findings clearly to non‑technical audiences, and identify when recurring requests should become permanent dashboards .
Desired Qualifications
• Bachelor’s degree in Economics, Finance, Data Analytics, Data Science, or Computer Science
• 4+ years of experience in data analysis, visualization, financial reporting, or dashboard creation
• Working SQL proficiency (joins, aggregations, grouping; window functions a plus)
• Strong attention to numerical accuracy
• Strong written communication skills
• Ability to read and reason about unfamiliar code
• Openness to AI‑assisted development tools paired with disciplined review
• Audience‑first mindset
• Curiosity about business operations (revenue, cost, churn, utilization, service levels)
Nice to Have
• Experience defining or maintaining metrics used by others
• Familiarity with analytical constructs (cohorts, ratios, period‑over‑period, mix shift, survivorship)
• Experience writing software (Python, JavaScript/TypeScript, R, C#, Java)
• Exposure to React, TypeScript, or modern front‑end frameworks
• Experience with columnar/cloud data warehouses (StarRocks, Snowflake, BigQuery, Redshift, ClickHouse)
• Data engineering or pipeline experience (ETL, Dagster, Airflow, Flink, Kafka)
• Familiarity with git, dbt, or lineage tools
• Background in operations, finance, or customer‑facing role .