Top Data & Analytics Jobs

The Business Analyst gathers and documents business and functional requirements, analyzes workflows, creates user stories and process diagrams, and translates stakeholder needs into buildable solutions. The role partners with Product, Engineering, QA, clients, and leadership throughout the product lifecycle, supporting backlog refinement, UAT, implementations, training, and feature rollouts. The analyst also identifies process gaps, risks, dependencies, and automation opportunities while maintaining accurate product and workflow documentation.

Leads the architecture, governance, modeling, and evolution of investment data platforms. Designs Snowflake structures, semantic layers, data products, metadata frameworks, quality controls, and AI-ready data foundations supporting portfolio management, research, trading, risk, reporting, and analytics. Partners with investment and technology stakeholders, documents architecture, establishes standards, and enables governed self-service and intelligent data consumption.

Build and oversee reliable ETL/ELT pipelines and data products that transform complex customer data into trusted analyses, visualizations, quality reports, and AI-powered insights. Responsibilities include data exploration, quality control, anomaly detection, AI/ML output evaluation, customer collaboration, documentation, and improving data-cleaning and analytics tools. The role requires cross-functional work in an Agile environment focused on security, data integrity, and clear communication.

Performs geospatial workflows using GIS, CAD, remote sensing, imagery, LiDAR, and surveying technologies. Develops and distributes vector datasets, aerial imagery, LiDAR products, and other high-quality geospatial data. Responsibilities include imagery preprocessing, feature digitization, LiDAR classification, metadata support, project reporting, geodatabase management, and advising on geospatial standards. Works independently and collaboratively to solve geospatial problems and maintain accurate data products.

Provides first-line BI support for tickets, emails, and incidents across business divisions. Designs, builds, and supports Power BI reports; triages stakeholder issues; manages SLAs; performs minor enhancements and bug fixes; communicates support performance; collaborates with IT teams; and identifies automation and process-improvement opportunities.

The Azure Senior FinOps Engineer optimizes cloud spending, manages Azure services, tracks financial performance, and supports application teams with data-driven insights.

Owns creation and maintenance of SKU and material master data in SAP ERP, including BOM and routing updates. Performs data audits, validation, reporting, and database support while assisting Supply Chain, Operations, Sales, R&D, and Finance. The role also maintains data procedures, supports process improvements, and ensures data accuracy, security, and confidentiality.

Leads the design, administration, optimization, and modernization of enterprise data platforms across SQL Server, Azure, and Microsoft Fabric. Responsibilities include database operations, high availability and disaster recovery, performance tuning, replication, cloud migrations, monitoring, security, governance, and automation. The role collaborates with architects and infrastructure teams, mentors junior engineers, and serves as a subject matter expert for database infrastructure and cloud architecture.

Designs and maintains Power BI reports and dashboards using Microsoft Fabric semantic models. Builds data models, writes and optimizes DAX, applies security controls, validates data quality, and creates certified datasets and reusable templates. Partners with stakeholders to define reporting requirements, presents insights, participates in peer reviews, and uses AI tools to improve analysis and delivery.

Leads the enterprise data management strategy, Data Operations organization, data governance, stewardship, quality, taxonomies, metadata, and master/reference data programs. Partners with engineering, product, business, regulatory, and audit stakeholders to improve data architecture, lineage, controls, lifecycle management, and commercialization of proprietary data assets. Oversees third-party data providers, automation initiatives, operating metrics, change governance, and organizational growth while preparing data for AI, machine learning, semantic search, and advanced analytics.