Top Data & Analytics Jobs

Owns performance measurement, recurring KPI reporting, dashboards, experiment measurement, forecasting, capacity models, business-case analysis, and data integrity for Operations initiatives. Partners with Growth, Engineering, Data, Product, Finance, and Operations leaders to explain metric changes, support strategic planning, and turn successful experiments into operating playbooks.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, reporting standards, adoption, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable, secure, trusted BI products. Manages and develops the BI team, prioritizes demand, translates business needs into delivery plans, monitors product value, and provides technical guidance on complex initiatives.

Leads complex data engineering workstreams and mentors engineers while designing scalable pipelines and cloud data infrastructure. Integrates marketing data from GA4, advertising platforms, CRMs, and CDPs into reliable datasets. Collaborates with machine learning teams on model training and serving, establishes engineering and data quality standards, and applies AI-enabled development workflows. Partners with stakeholders to deliver product-minded data solutions and drives process improvements, documentation, monitoring, and knowledge sharing.

Own Savvy’s end-to-end financial and operational data architecture, including centralized modeling, governance, metric definitions, data quality, reconciliation, reporting automation, and self-service BI adoption. Partner with finance, operations, compliance, engineering, and executives to establish durable data systems and technical direction. Help shape and scale the company’s data function and potentially build an early-stage team.

Leads business performance reporting and analytics for Mars’s salty snacks portfolio. Owns dashboards, scorecards, and KPI reports; translates complex data into actionable insights and strategic recommendations; analyzes category, brand, competitive, and syndicated data; collaborates with finance, marketing, commercial, and consumer insights teams; and presents executive-ready recommendations to internal and external stakeholders.

Leads product metadata strategy, governance, taxonomy, standards, and quality across publishing products and sales channels. Designs data models, validates records, manages ONIX feeds and identifiers, improves discoverability, coordinates corrections, and integrates rights information. The role collaborates with IT, marketing, sales, editorial, distribution partners, vendors, and industry standards organizations while guiding cross-functional adoption without direct supervisory authority.

Analyzes and validates enterprise datasets using SQL, investigates discrepancies, traces data lineage through ETL/ELT pipelines and warehouses, and documents mappings, transformations, definitions, and data quality findings. Collaborates with business stakeholders, Data Engineering, and BI teams to identify root causes and improve data accuracy, consistency, and transparency. The role emphasizes hands-on data investigation rather than dashboard development or governance policy management.

Manages the firm's matter-related data assets, including matter profiles, experience data, knowledge management products, dashboards, and reporting. Oversees data quality, validation, platform administration, stewardship procedures, and process improvements. Partners with attorneys, practice groups, marketing, pricing, and data teams to translate business needs into data products and support AI and transformation initiatives. Supervises and develops direct reports while ensuring confidentiality, operational coverage, and compliance with firm policies.

The Data Engineer will architect, build, and optimize enterprise data platforms, lakehouse architectures, batch and streaming pipelines, analytics-ready data models, and governed semantic layers. Responsibilities include implementing Unity Catalog governance, security, lineage, CI/CD, automated testing, monitoring, and reliable production operations. The role partners with analysts, BI developers, and business stakeholders to deliver scalable solutions using Microsoft Fabric, Azure Databricks, Azure services, Power BI, and potentially Snowflake.

Translate business requirements into scalable reporting and analytics solutions. Partner with SMEs and engineering to source, validate, and model data in Azure and Microsoft Fabric. Build and maintain Power BI (primary) and Tableau dashboards, perform data profiling and quality checks, document lineage and definitions, and participate in Agile delivery to enable data-driven decisions for Medical Stop Loss operations.