Top Entry Level Data Management Jobs

Designs conceptual, logical, and physical data models for R&D research and clinical domains. Translates scientific and business requirements into reusable, scalable, AI-ready data structures that support analytics, machine learning, data integration, and standardized workflows. Partners with domain experts, data engineers, architects, data scientists, and governance teams to apply enterprise standards, schemas, ontologies, metadata, quality rules, and lineage. Promotes shared data assets and ensures models are implementable, interoperable, and aligned with evolving R&D needs.

Leads enterprise data-quality governance for the War Data Platform, establishing standards, automated controls, monitoring, compliance reviews, and audit readiness. Directs a cross-functional quality team, investigates root causes, manages remediation, oversees contractor and vendor performance, and coordinates with engineering, cybersecurity, acquisition, senior leadership, and oversight organizations. The role ensures mission-critical datasets are accurate, reliable, available, traceable, and suitable for analytics and AI applications.

Manages debris-monitoring data, ticket reconciliation, quality assurance, reporting, documentation, and invoice discrepancy review. Tracks reconciled, unreconciled, and voided load tickets; coordinates with hauling contractors and clients; maintains project records; prepares payment recommendations and closeout documentation. The role requires exceptional Microsoft Excel skills, debris-monitoring knowledge, accurate data analysis, strong communication, and the ability to work extended hours in demanding response conditions.

Leads a data engineering team delivering secure, scalable data platforms, pipelines, semantic layers, and analytics products. Oversees architecture, governance, data quality, observability, CI/CD, stakeholder alignment, delivery planning, and engineering standards. Develops technical talent, drives modernization and AI/ML readiness, supports cloud and platform evolution, and ensures trusted data assets meet enterprise reporting and decision-making needs.

Manages financial aid systems, databases, SQL queries, reports, dashboards, integrations, automation, and data quality. Troubleshoots complex technical issues, supports Banner and related enterprise systems, administers compliant financial aid processes, and coordinates upgrades and testing. Leads process improvement initiatives, trains staff, documents technical procedures, and collaborates with IT, vendors, and campus stakeholders. Provides financial aid customer service and counseling while supporting regulatory compliance and operational reporting.

Downloads, verifies, compiles, and analyzes datasets to support CDMRP data operations. Validates data quality and completeness, documents data pulls, creates visual process maps, and tracks incoming requests and deliverables. Requires basic SQL skills and proficiency with Visio, Excel, and Access, along with U.S. citizenship and eligibility for NACI and ADP III designation.

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.

Partners with Product leaders to solve ambiguous business problems through forecasting, modeling, segmentation, cohort analysis, scenario analysis, dashboards, and executive insights. Owns analytical initiatives from problem framing through implementation and measurable outcomes. Uses SQL across large enterprise datasets and applies generative AI and LLM tools to analyze structured and unstructured data, while validating AI-generated outputs. Prioritizes analytics requests, improves recurring workflows, and communicates recommendations to senior stakeholders.

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.

Manages wildfire debris-removal data, including field-data quality assurance, load-ticket reconciliation, invoice discrepancy identification, reporting, and project-document control. The role coordinates reconciled and voided tickets with contractors, prepares payment recommendations, exports client reports, maintains project records, and supports closeout activities. Work occurs in remote Alaska with extended shifts, weekends, and potentially 70–90 hours per week during the response period.

Leads OpenAI’s Growth & Revenue data engineering team, owning data strategy and delivery across growth, subscriptions, billing, payments, monetization, and revenue. Builds and manages a high-performing team, develops reliable and well-modeled data products, establishes trusted metrics and quality standards, and partners with Data Science, Product, Finance, and Engineering. The role also oversees roadmap planning, privacy, governance, observability, incident response, stakeholder communication, and team hiring and development.

Manage and curate clinical, biospecimen, experimental, raw, and derived scientific data for a biomedical research laboratory. Maintain institutional and cloud data resources and scientific websites, support open science and FAIR principles, contribute to grants and manuscripts, train lab members, and attend scientific conferences. The role requires careful data management, collaboration with researchers and engineering staff, strong communication, and the ability to manage shifting priorities in an in-person academic environment.

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 server-side tagging, marketing pixel, and CAPI implementations for clients. Responsibilities include architecture, QA, troubleshooting, UAT, implementation documentation, data quality support, stakeholder training, and coordination with client development teams. Serves as the technical advisor for Tealium, Adobe Experience Platform Tags, Google Tag Manager, and related tracking infrastructure. The role also manages client relationships, supports measurement strategy, and develops one to two direct reports.

Manage and mentor a data engineering team while leading Snowflake-based platform architecture, enterprise data integrations, governance, observability, and pipeline reliability. Partner with analysts, business leaders, product management, and engineering teams to improve trusted self-service data access. Establish engineering standards, modernize the data stack, optimize costs, and deliver an AI-ready data foundation supporting analytics, reporting, and future AI initiatives.

Manage the ASISTS enrollment system, enter and maintain student and attendance data, prepare reports for analysis, follow up for outcomes, support intake/registration/testing, assist instructors, develop outreach materials, and complete required trainings.

The Data Manager will develop dashboards, conduct statistical analyses, and support compliance through data management and risk assessments to enhance organizational performance.