Top Data & Analytics Jobs

Own the Business Intelligence domain by building scalable data models, dashboards, reports, and data pipelines. Partner with Product, Sales, Operations, Data Engineering, and leadership to ensure data quality and support decisions. Analyze large datasets, run experiments, develop predictive models, improve analytical infrastructure, and mentor colleagues. The role requires advanced SQL, data warehousing, ETL/ELT, scripting, visualization, cloud architecture, and governance expertise.

Design and optimize Databricks ETL/ELT pipelines on Azure using PySpark, SQL, Delta Lake, and Kafka. Build CDC and near-real-time processing solutions, ingest data from diverse sources, implement data quality controls, and apply SCD Type 1 and Type 2 modeling. Automate workflows with Databricks Workflows and GitHub-based CI/CD while collaborating in an Agile environment.

Conduct primary and secondary research on innovation in corporate legal departments. Build relationships with senior legal professionals, lead interviews and roundtables, collect and validate proprietary intelligence, manage structured datasets, monitor industry trends, analyze qualitative and quantitative findings, and translate research into actionable insights, reports, articles, and executive-facing content.

Analyze POS, loyalty, panel, and syndicated data to identify consumer and category insights. Develop assortment, item performance, and store-clustering recommendations that support sales, market share, and category growth. Partner with clients and business leaders on data-driven strategies, translate findings into business opportunities, and present performance reviews. Collaborate with sales, category management, and analytics teams on strategic planning.

Supports data and analytics projects by designing ETL processes, developing data pipelines, integrating and validating data, and improving data quality. Creates Power BI reports and dashboards, troubleshoots data and storage issues, and helps enhance data warehouse and analytics solutions. The intern also explores AI-enabled tools, cloud platforms, and modern data engineering practices while collaborating with business partners.

Develops and maintains validated datasets, dashboards, automated reports, analytical models, and business insights for freight-forwarding planning and operations. Extracts and reconciles SAP, Genisys, LOTS, financial, and operational data; analyzes KPIs, revenue, costs, margins, shipment activity, and data quality. Translates reporting requirements into repeatable processes, supports system enhancements and testing, documents data logic, and guides analyst-level resources.

Analyzes business and application requirements, documents process changes, manages projects, supports software testing, resolves client issues, and develops reporting for multiple business functions. Partners with stakeholders to improve processes, tools, and reporting while supporting existing applications and maintaining strong communication, organization, accuracy, and customer service.

Design, build, validate, and support reliable data solutions for enterprise operations and analytics. Responsibilities include developing pipelines and transformations, translating business requirements into technical solutions, implementing data quality checks and monitoring, tuning SQL and processing jobs, documenting data definitions and lineage, and supporting security, access controls, reconciliation, and failure recovery. The role collaborates with stakeholders across the delivery lifecycle to ensure accurate, maintainable, and governed data.

Designs and manages database architectures, schemas, dictionaries, migrations, performance monitoring, backups, recovery, security, and documentation. Collaborates with developers, analysts, and administrators to maintain data integrity and support applications. Requires extensive database engineering or administration experience, SQL proficiency, knowledge of major database systems, cloud databases, cross-domain solutions, and big data environments. An active TS/SCI clearance with full-scope polygraph is mandatory.

Design and build scalable data pipelines, migrations, integrations, curated datasets, semantic models, dashboards, and analytics products. Evolve cloud-native lakehouse platforms, establish data quality and performance practices, and deliver trusted, AI-ready insights. Partner with technical, product, and insurance-domain stakeholders to translate business needs into reliable data solutions. The role requires deep property and casualty insurance expertise, extensive data engineering experience, and ownership of complex technical problems.