Top Data Management Jobs in Seattle, WA

Leads and coaches a data engineering team supporting finance analytics. Oversees data warehouse, ETL, cloud data management, analytics solutions, and engineering project delivery. Ensures reliable, high-quality pipelines and accurate stakeholder reporting while providing technical guidance, shaping data strategy, and driving cross-functional initiatives with senior leaders.

Leads the People data ecosystem, including Snowflake workforce data models, pipelines, governance, metric certification, and data quality. Develops scalable workforce analytics products using Visier and Snowflake, enables governed AI-driven insights, replaces manual reporting with self-service solutions, and manages a high-performing team of data and analytics professionals.

Leads the Data Engineering team, manages priorities and delivery, and partners with analytics, data science, and business stakeholders. Oversees scalable ETL/ELT pipelines, data platforms, warehousing, streaming, reliability, incident response, security, governance, and compliance. Drives engineering standards, CI/CD, testing, Agile practices, cost optimization, architecture decisions, and continuous improvement while mentoring engineers and ensuring dependable data operations in an Azure environment.

The Compliance Data & Analytics Manager develops AI and automation prototypes, integrates disparate data sources, builds Python and SQL analytics workflows, and creates web applications and automated alerts for compliance risk intelligence. The role partners with Legal, Finance, Regulatory Affairs, data science, and business intelligence teams to improve risk models and translate regulatory requirements into actionable analytical solutions.

Owns Kestra’s enterprise data platform, Microsoft Fabric transition, data architecture, governance standards, and Master Data Management program. Leads platform reliability, semantic models, self-service BI enablement, data protection, compliance, vendor resources, and technical teams. Advises executives and functional data owners while preparing governed data assets for AI, automation, and enterprise reporting.

Leads a data integration team responsible for onboarding, loading, monitoring, and securing client and vendor data feeds. Oversees Boomi, SQL, and Python integrations; manages feed quality, scheduling, exports, documentation, SLAs, and issue resolution. Partners with clients, vendors, client success, and internal data teams while mentoring analysts and improving automation, transparency, scalability, and anomaly detection across SQL Server and Snowflake environments.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Senior Data Manager acquires, validates, integrates, protects, and manages enterprise data throughout its lifecycle. The role develops ETL solutions, data architectures, models, stored procedures, reporting datasets, and visualizations using Databricks, SQL, and cloud technologies. Responsibilities include translating business needs into technical requirements, leading data projects through deployment, analyzing complex data, improving processes, and supporting business decisions through accessible insights.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Leads and grows the data engineering team while owning enterprise data architecture, ingestion, modeling, semantic layers, governance, secure APIs, and reliable platform outcomes. Partners with finance, operations, sales, marketing, and product to deliver governed, traceable data for products and AI agents. Sets the roadmap, manages vendors and costs, reviews architecture, contributes code, and delivers cross-functional data platform projects.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Manage and grow Ashby’s data analytics team while remaining hands-on with analytical work. The role includes hiring and coaching analysts, improving data practices, prioritizing requests, developing specialization, maintaining analytical quality, and guiding responsible AI adoption. The manager will work across raw and modeled data, dbt models, metric definitions, dashboards, and internal data products, partnering closely with business teams in a remote, high-growth B2B SaaS environment.

Analyzes and consolidates data from multiple sources, establishes KPIs, builds dashboards, and automates reporting for the W&J Industrial Department. Supports leadership with performance reviews, executive presentations, strategic analyses, and decision-support materials. Coordinates information gathering and monitors cross-functional initiatives while improving data quality, reporting efficiency, and business intelligence capabilities.

Lead and grow data engineering and analytics engineering teams while overseeing data platform modernization, BigQuery and Looker migrations, reusable dbt models, self-service capabilities, governance, reliability, and data foundations for AI and ML. Partner with technical and business stakeholders to prioritize roadmaps, manage hiring and performance, improve adoption, and protect sensitive healthcare data.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Leads a seven-person operational data engineering team responsible for APIs, relational data platforms, legacy and migrated data integration, and transactional data scalability. Establishes priorities with product and technical stakeholders, provides technical guidance, manages delivery risks and resources, improves operational reliability, and develops team capabilities. The role partners across Engineering, Architecture, Product, Security, Infrastructure, Operations, vendors, and business stakeholders to deliver scalable data solutions aligned with organizational objectives.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Leads data analytics projects that generate insights for strategic decision-making. Develops visualization solutions with Power BI and Tableau, builds data pipelines, applies statistical modeling and predictive analytics, and manages data integrity and security. Collaborates with clients on tailored data solutions while coaching analytical teams, managing accounts, overseeing project success, and identifying business opportunities.

Own the go-to-market master data management roadmap and governance model for accounts, contacts, and organizational hierarchies. Define golden record, matching, merging, survivorship, data quality, stewardship, and SLA standards across Salesforce, billing, finance, marketing, product, support, and warehouse systems. Partner with engineering, systems, finance, legal, and security teams to implement integrations, privacy controls, data products, and remediation programs. Report data health, risks, and business impact to leadership.

Leads Marketing's data architecture, metric governance, analytical modeling, predictive modeling, experimentation, and executive performance reporting. Manages three to four analysts while remaining hands-on with advanced SQL, Snowflake data validation, dimensional modeling, cross-system reconciliation, attribution, customer analytics, and AI-assisted natural-language analytics. Partners with engineering, governance, product, and marketing teams to define data products, ensure analytical accuracy, and establish scalable measurement standards.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Manage and develop a team of 4–6 analysts delivering customer reporting and analytics. Lead complex analyses, establish standards for rigor and reproducibility, oversee project delivery, present findings to stakeholders, and partner with Product and Engineering on measurement products and AI-enabled analytics tools. The role requires deep advertising measurement expertise, client-facing communication, dashboard development, and hands-on proficiency in SQL, Python, Excel, statistical methods, and analytics platforms.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.