Top Senior Data & Analytics Jobs

Build and maintain enterprise workflow applications, relational data structures, data pipelines, SQL logic, REST integrations, dashboards, and reporting outputs for a federal health client. Translate user stories into functionality, validate data, support testing, document solutions, and collaborate in Agile delivery while meeting federal security, privacy, records management, and accessibility requirements.

Implement and maintain Informatica data governance solutions, including metadata management, data quality, lineage, and stewardship workflows. Develop automated ingestion, transformation, and validation processes; integrate Snowflake with Informatica and cloud platforms; monitor pipeline reliability; document governance standards; support reporting; troubleshoot data issues; and provide technical guidance to business and technical teams.

Develop and support SAP BRIM data migration solutions using BODS and EMIGALL. Responsibilities include source-to-target mapping, ETL development, data cleansing, validation, reconciliation, migration testing, SAP integrations, SQL analysis, production support, documentation, and cutover activities. The role collaborates with architects, functional consultants, infrastructure teams, and business stakeholders while supporting SAP S/4HANA, FICA, billing, and customer account migrations.

Senior individual contributor leading Sales BI strategy and AI transformation. Responsibilities include developing enterprise Power BI dashboards and data models, defining sales metrics, delivering production AI agents and automated analytical workflows, shaping Snowflake and AI analytics infrastructure, leading cross-functional initiatives, mentoring analysts, and influencing sales executives through data-driven recommendations. The role requires measurable adoption and business impact from AI-enabled analytics, without direct people-management responsibility.

Build and support AWS data lake and Snowflake solutions, develop Python and Spark data pipelines, automate infrastructure with Terraform, and manage CI/CD deployments. The role uses AWS services including Glue, S3, Lambda, Step Functions, and Lake Formation, along with monitoring and change-management tools. Candidates will also apply AI-assisted engineering tools to improve productivity and may work with Databricks, Unity Catalog, and cloud analytics platforms.

Own end-to-end analytics solutions for Vay’s operations and mobility teams, including SQL/dbt data modeling, BI dashboards, alerts, KPI definition, and actionable insights. Improve fleet readiness, maintenance, charging, vehicle positioning, customer experience, and operational efficiency. Partner with operational and product leaders, collaborate with Data Science, and build scalable data foundations using cloud warehouses and modern data tooling.

Design and implement attribution, source tracking, CRM integrations, ROI measurement, funnel reporting, and sales performance systems for B2B clients. Consult with revenue leaders, define metrics, build and validate reporting across marketing, sales, CRM, advertising, and BI platforms, troubleshoot data quality issues, document solutions, and train client teams. Contribute to implementation methodologies, technical content, automation, and AI-enabled data validation and analysis.

Designs and delivers end-to-end enterprise data solutions on a GCP-native platform, covering ingestion, transformation, modeling, security, quality, and analytics consumption. Defines data mappings, dimensional models, and platform patterns; selects GCP services; guides engineers; reviews implementations; and translates business requirements into executable designs. The role also produces architecture documentation, supports modernization and EDW migration, collaborates across technical and business teams, and contributes to AI-ready data products and Agile delivery practices.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Leads quantitative and predictive analytics, data modeling, campaign optimization, and business insight generation for personal financial services. Partners with product and marketing teams to identify acquisition, retention, cross-sell, and sales opportunities. Builds analytical models, dashboards, reporting frameworks, and executive-ready recommendations using SQL, Python, R, SAS, Tableau, and Power BI. Translates business requirements into data architectures and aligns analytics initiatives with strategic and financial goals.