Top Data & Analytics Jobs

MetLife is seeking a Big Data Engineer to support its AI-enabled, people-centered transformation within the financial services industry. The provided description does not include specific day-to-day responsibilities or qualifications.

Supports Fund Management through regulatory communications, cost allocation, operational reporting, and analytics. Develops and maintains Access, Excel, SQL, and enterprise reporting solutions; integrates data across systems; improves data quality and workflows; and supports testing, validation, deployment, automation, and AI-enabled process enhancements. The role also serves as a technical subject matter expert and coordinates regulatory reporting while driving efficiency and cost savings.

Support a book of business by validating, transforming, and reconciling data, managing daily processing and file audits, generating reporting outputs for outreach, creating file configuration specs, resolving discrepancies with stakeholders, and driving process improvements to ensure regulatory compliance and operational efficiency.

Leads advanced analytics, data preparation, BI dashboard development, data modeling, ETL/ELT integration, and data quality automation. Partners with stakeholders to deliver scalable Power BI and Power Platform solutions, promotes AI-enabled automation and process optimization, supports governance and compliance, aligns with platform vendors, and mentors junior team members. Requires strong Power BI, DAX, Power Query, SQL, data modeling, and Azure experience, with Python/R and data science knowledge preferred or advantageous.

Leads the design, administration, and expansion of Workiva Wdata across the enterprise. Curates governed datasets, builds queries and views, automates ingestion and transformation workflows, integrates ERP and warehouse data, and ensures data quality, lineage, reconciliations, and audit-ready reporting. Partners with Finance, Actuarial, Risk, Compliance, and IT to deliver scalable financial and regulatory reporting solutions, establish governance standards, create reusable templates, and support training and adoption.

Lead enterprise data engineering strategy and roadmap to build scalable cloud-native data platforms. Oversee design and modernization of data architectures, pipelines, and integration. Ensure data security, privacy, and governance, incorporate AI/ML, and drive data democratization. Lead global teams, collaborate with business and technology leaders, and deliver enterprise-wide data capabilities to enable analytics, innovation, and business growth.

Leads data governance standards, policies, metadata, business glossaries, lineage, critical data elements, governance metrics, and regulatory alignment. Resolves governance issues, maintains governance artifacts, and collaborates across business, technology, operations, and analytics teams. The role independently leads solution design and estimation while coaching and developing data governance talent.

Build and deploy Alteryx workflows for automated data processing, transformation, and integration. Diagnose workflow performance issues, conduct root cause analysis, and collaborate with business, technology, operations, data governance, data quality, data modeling, architecture, data science, and business intelligence teams. This individual contributor role operates under senior guidance and requires SQL, Excel, VBA, and Alteryx expertise.

Design and build enterprise Azure data platforms using Synapse, Databricks, ADLS Gen2, PySpark, Spark SQL, and Data Factory. Lead modernization and migration initiatives, develop scalable pipelines, implement data quality and governance practices, optimize performance and cloud costs, and establish architecture and coding standards. Mentor engineers and promote AI-assisted development. Preferred experience includes Informatica, streaming technologies, Terraform, Power BI, AI/ML integration, and insurance or financial services.

Designs and delivers enterprise-scale Azure lakehouse platforms, data products, ETL/ELT and streaming pipelines using Databricks, Spark, Delta Lake, and related Azure services. Leads and mentors data engineers, establishes engineering standards, drives Agile delivery, and collaborates with technical and business stakeholders. Implements CI/CD, security, governance, monitoring, data quality, lineage, observability, performance tuning, and cost optimization for production data platforms.