Top Remote Data Management Jobs

Design and maintain scalable HR data architecture in Snowflake; build and optimize ETL/ELT pipelines with Matillion; enforce data governance, quality, lineage and security; manage SQL Server metadata environments; implement DevOps for data assets; partner with stakeholders and support AI-ready semantics and reusable data products.

Leads a team of data engineers responsible for building and scaling Niche’s data platform. Oversees data pipelines, warehouse layers, platform reliability, data quality, monitoring, and engineering best practices. Manages roadmap execution, Agile rituals, cross-functional collaboration, hiring, mentoring, and career development. The role also drives process improvements, operational excellence, scalability, and delivery of secure, observable data solutions supporting analytics, reporting, content, and operational systems.

Leads enterprise architecture for data, analytics, and AI/ML platforms. Defines cloud, Lakehouse, streaming, governance, integration, and machine-learning architecture standards; guides modernization, proof of concepts, platform scalability, security, and cost optimization. Partners with executives, product owners, cybersecurity, governance, and engineering teams while leading design reviews, architecture forums, and technical programs. Requires deep experience with Databricks, cloud-native data platforms, distributed systems, data governance, and enterprise-scale architecture.

Designs and governs enterprise-scale data and AI architectures using Databricks and Lakehouse technologies. Responsibilities include Medallion Architecture, semantic layers, data modeling, SAP ECC to S/4HANA integration, ETL/ELT, batch and streaming ingestion, governance, lineage, quality, security, and platform modernization. The role partners with engineering, analytics, AI/ML, SAP, security, and business teams while providing technical leadership and mentorship.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.

Leads a data engineering team responsible for enterprise data platforms, lakehouse architecture, production pipelines, governance, security, reliability, and operational excellence. Combines people leadership with hands-on technical guidance across AWS, Snowflake, SQL, Python, data quality, observability, and compliance. Partners with scientific, clinical, product, analytics, security, and IT teams to deliver scalable, trusted data capabilities while managing priorities, technical debt, vendors, and team development.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages agile sprint planning, release delivery, DevOps metrics, and cross-functional project plans. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, manages team members, and ensures reliable, well-governed data solutions for business intelligence and reporting.

Leads end-to-end data architecture, engineering pipelines, ETL, data modeling, quality monitoring, and Tableau BI platform operations. Partners with stakeholders to define requirements, manage project plans, lead agile sprints, and deliver reliable data solutions. Establishes governance, security, performance, and continuous improvement practices while developing AI-enabled analytics capabilities. Mentors data engineers and manages team performance, documentation, dependencies, and delivery across multiple workstreams.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Lead and mentor data engineering and DBA teams while driving GCP-based streaming and batch data platform initiatives. Oversee BigQuery, dbt, Apache Flink or Dataflow, data quality, testing, observability, governance, reliability, and cloud cost optimization. Remain hands-on with coding, code reviews, architecture, and complex system problems while aligning data infrastructure with business and product goals. Champion AI-assisted engineering and automation across the platform.

Lead the data engineering squad and oversee the DBA team while driving GCP-based streaming and batch infrastructure projects. Build and review code, establish standards for data quality, testing, observability, governance, and cost optimization, and align data platforms with business goals. The role requires expertise in GCP, BigQuery, dbt, Apache Flink or Dataflow, relational databases, AI-assisted engineering, and team leadership.

Lead the data engineering squad and oversee the DBA team while remaining hands-on with platform projects. Drive streaming and batch infrastructure using GCP, BigQuery, dbt, and Apache Flink or Dataflow. Establish standards for data quality, testing, observability, governance, documentation, and cloud cost optimization. Promote AI-native engineering practices, ensure transactional database reliability, mentor engineers, and align data platforms with business and product goals.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

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.

Leads data analysis, reporting, performance evaluation, and dashboard development for federal transition assistance programs. Manages data integration, modeling, quantitative and qualitative analysis, program evaluations, executive reporting, and performance measurement. Translates complex data into actionable recommendations supporting operational effectiveness, strategic planning, modernization, and continuous improvement. Collaborates with government leaders, program managers, technical teams, and stakeholders. The role is remote with occasional travel for in-person meetings.

Leads public financial management data analysis, fund-flow and expenditure reconciliation, fiduciary risk assessment, and verification support in Uganda. Produces dashboards, exception reports, risk flags, and evidence summaries from financial, HRIS, and administrative data. Supervises and trains analysts and verification teams, coordinates with government and project stakeholders, maintains audit trails, and identifies issues requiring targeted field verification.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Leads enterprise analytics strategy, data integration, governance, reporting, dashboards, forecasting, and advanced business analysis. Manages analysts and partners with Sales, Pricing, Finance, Product Management, Operations, and executive leadership to translate complex data into actionable recommendations. Oversees Power BI dashboards, KPI frameworks, data quality, predictive modeling, and reporting automation to improve growth, profitability, pricing, and operational performance.

Leads R&D data stewardship across metadata, cataloging, data products, profiling, quality, governance, and compliance. Uses Informatica, SQL, Databricks, Python, and PySpark to curate data, automate workflows, define quality controls, and resolve complex issues. Applies AI-assisted stewardship and semantic data concepts while collaborating with technical and business stakeholders. Coaches other stewards, supports audit readiness, and improves stewardship standards and operating practices.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

Leads and develops product, marketing, and data analysts while overseeing analytics strategy, prioritization, technical standards, experimentation, reporting, and data quality. Partners with Product, Marketing, Finance, Engineering, and recruiting to deliver trusted insights, scalable self-service analytics, and team growth. Requires strong SQL and Python skills, modern data-tool experience, analytics leadership, stakeholder communication, and at least five years in data roles with two years managing teams.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.