WHAT DOES A DATA MANAGER DO?

Published: October 02, 2024 - The Data Manager orchestrates the evaluation and management of data to bolster the Field Services Program, involving data collection, cleaning, and analysis using SAS to create detailed reports and presentations. This role entails developing and refining data services and pipelines, alongside enhancing data capabilities in collaboration with Engineering Managers, to support comprehensive field services activities and compliance with program protocols. Additionally, the position involves presenting analytical outcomes at various levels and contributing to initiatives aimed at reducing HIV disease transmission through strategic interventions and professional engagement at national conferences.

A Review of Professional Skills and Functions for Data Manager

1. Data Manager Duties

  • Database Development: Develops and manages computerized databases appropriate to the design of various research studies.
  • Data Mapping: Maps data between different databases.
  • Data Validation: Validates and assures data is captured accurately.
  • Consultation: Consult with departmental personnel for problem definition and management requirements.
  • Data Analysis: Analyzes source documents, database structure, and management report requirements.
  • System Coordination: Coordinates systems improvements between Information Systems and user departments and provides necessary documentation and consultation for implementation of the system.
  • Research Participation: Participates in various scientific research projects to transform the approach to cancer therapy through research, integrating germ line, molecular, and genetic information with disease-specific biology to bring personalized cancer therapy to the clinic.
  • Query Design: Designs simple to complex queries using structured query language.
  • System Development: Develops systems to permit significant flexibility in the types of queries performed.
  • Query Execution: Performs queries related to disease site parameters of molecular and clinical outcomes, across disease site parameters comparing and contrasting, identifying trends in molecular data and in finance data.
  • Problem Solving: Assists in problem-solving and formulation and testing of hypotheses and complex analysis of data.
  • Project Support: Assists ICT database team in daily operation of several information technology projects to support the ICT department and CCTT clinic.
  • IT Training: Provides information technology education and training to ICT faculty and staff.

2. Data Manager Details

  • Data Leadership: Lead a data group consisting of highly engaged data teams.
  • Tech Strategy: Lead the development as well as define the tech roadmap and strategy of Kenshoo’s data architecture and content capabilities.
  • Stakeholder Collaboration: Collaborate with key business stakeholders to identify projects and needs, and define business prioritization across the company.
  • Data Migration Support: Assist the government in guiding the migration of operational data from legacy Oracle data stores to a cloud-ready architecture.
  • Coordination: Coordinate between government leadership, development teams, vendors, and system users to ensure system planning, design, and implementation meet mission needs and resource constraints.
  • Risk Management: Identify, track, and report project and system risks.
  • Documentation Maintenance: Create and maintain systems engineering documentation related to the overall program.
  • Documentation Review: Review and assess systems engineering documentation generated by development teams.
  • Collaboration: Collaborate with other mission areas and the customer Enterprise Architecture Office regarding challenges related to data management.
  • Reporting: Document accomplishments and insights via documentation and other coordination to include trip reports, monthly status reports, collaboration exchanges, program management reviews, and end-of-task reporting.
  • Data Cataloging: Carry out searches of publicly available online information using predefined methodologies and catalog data for data abstraction and entry.
  • Data Structuring: Transform paper and other unstructured data and information into structured, analyzable formats.
  • Data Entry: Scan paper records, manually type, paste from PDF or other file formats into a structured IT system, and run automated extraction scripts or other methods.
  • Quality Assurance: Perform continuous quality assurance of data using customized detection algorithms or off-the-shelf techniques, researching anomalies, identifying root causes, preparing reports of metrics and outcomes, and recommending solutions.

3. Data Manager Responsibilities

  • Quality Management: Development, implementation, and management of quality, safety, and performance metrics for facilities.
  • Trend Identification: Identification of trends and opportunities for improvement.
  • Reporting: Responsible for reporting (internal and external).
  • Compliance Assurance: Assure compliance with all accreditation reporting requirements internally and to external agencies including Joint Commission, CMS, and others.
  • Data Analysis: Interpretive and comparative data analysis to inform Division strategic planning and decision-making using individual facility, state, regional, and national measures.
  • Information Integration: Analysis of program-related data, research, and integration of information from relevant and reliable sources.
  • Policy Alignment: Alignment of oversight agencies, policies, and regulations to support project management and implementation responsibilities.
  • Outcome Evaluation: Expansion of system-wide mechanisms for evaluating outcomes.
  • Data Management: Management of ad hoc data requests, public records requests, and legislative inquiries.
  • Dashboard Development: Development, management, and oversight of performance dashboards and metric scorecards.
  • Project Direction: Provide direction to Division and Facility Management for project planning and program implementation.

4. Data Manager Job Summary

  • Data Evaluation: Evaluating and managing data to support the Field Services Program.
  • Data Management: Collecting, cleaning, and coding data using SAS.
  • Data Analysis: Analyzing data and preparing summaries as directed, including reports, manuscripts, and presentations, which may include tables, graphs, and maps.
  • Field Support: Supporting field services activities through questionnaire/database development, data entry, and data analysis and other projects.
  • Communication: Communicating with medical facilities to ensure completion of onboarding protocols related to re-engagement activities.
  • Protocol Compliance: Ensuring compliance with Field Service Program protocols.
  • Data Updates: Ensuring compliance with data updates and exchanges.
  • Presentation Skills: Presenting analytic findings in various settings including AACO, state, or national meetings.
  • Intervention Development: Contributing to the development of interventions to reduce HIV disease transmission.
  • Representation: Representing AACO at local, regional, state, and national professional meetings and conferences.
  • Collaboration: Working with other Engineering Managers to continuously improve Kenshoo’s data capabilities and promote relevant frameworks and tools.
  • Feature Execution: Leading execution of features and complicated data models, data services, data pipelines, and APIs from inception to production.
  • Team Development: Setting the pace for the personal growth of both engineers and team leads in the group, providing support and mentoring.

5. Data Manager Accountabilities

  • Vendor Management: Assist in vendor management/oversight.
  • Database Oversight: Assist in oversight of database design.
  • Specification Review: Assist in the review and creation of edit check specifications.
  • CRF Design: Assist in CRF design/review.
  • Data Accuracy Review: Review clinical data for accuracy.
  • Data Management Planning: Assist in the creation/review of data management plans.
  • Coordination: Assist in coordinating activities with statistics and programming for DM deliverables.
  • User Testing: Assist in user acceptance testing for CDMS and IXRS systems.
  • Quality Tracking: Track quality issues and general data trends.
  • Data Filing: Ensure adequate filing and archiving of relevant data and documentation related to DM.
  • SOP Development: Assist in the development of SOPs and work instructions.
  • Training Support: Assist in EDC training for co-workers, site staff, and CRAs.
  • Safety Review Facilitation: Assist in facilitating interim safety reviews.

6. Data Manager Functions

  • Requirements Definition: Work with various data analysts and stakeholders around the company to define functional and non-functional requirements for data pipelines and analytics projects.
  • Data Standardization: Maintain a standardized set of data sources available to analysts through Tableau Server and Research database.
  • Infrastructure Design: Help design and build next-generation infrastructure with reliable data pipelines that make data from a variety of sources (MySQL databases, third-party tool databases, REST APIs, surveys, Salesforce, Eloqua) accessible for analysis.
  • Measure Assessment: Conduct ongoing assessments and revisions of selected measures, definitions, and consistency in reporting across all facilities.
  • Quality Oversight: Oversee state and local personnel in the use of data to monitor the quality of state programs and promote improvement among facilities across the continuum.
  • Data Support: Support all teams of DSOHF in data, analysis, strategic planning, facility scorecard reporting, departmental and legislative data reporting, and other reports.
  • Operational Oversight: Provide operational oversight, system planning, technical assistance, and act as a liaison to facilities.
  • Initiative Management: Manage key Division initiatives pertaining to facilities.
  • Representation: Represent facilities to internal and external customers, accreditation organizations, oversight agencies, and community stakeholders.
  • Team Development: Inspire and develop a collaborative team of data experts, maximizing potential through coaching, continuous learning, excellent communication, and effective ways of working.
  • Collaboration: Build strong working relationships and collaborate with teams in Information Services, Operations, Digital, and Income, working on cross-team projects.
  • Account Management: Act as the key account manager for the fundraising CRM (ThankQ), maximizing relationships with external agencies.

7. Data Manager Job Description

  • Initiative Deployment: Provide the Zone and Group Data teams with a focal point for the deployment of major initiatives into the UKI hub.
  • Impact Analysis: Conduct impact analysis on the current landscape and processes of data products coming from the group or zone.
  • Integration Requirements: Identify local integration and migration requirements.
  • Backlog Management: Ensure progress on backlog items with local deliverables.
  • Risk Mitigation: Mitigate project risks and escalate as necessary.
  • Stakeholder Communication: Provide UK stakeholders with a focal point for data requirements.
  • Tool Portfolio Examination: Examine our portfolio of strategic tools for opportunities to respond to these requirements.
  • Requirement Differentiation: Separate the truly local requirement from the yet-to-be-delivered roadmap.
  • Request Transformation: Understand business requests and transform them into technical requirements for the data engineers.
  • Testing Oversight: Ensure that the engineers have completed reasonable testing before UAT.
  • Project Communication: Provide timely communication on all aspects of project work to all stakeholders in conjunction with PMs from Zone or Group.
  • Support Assurance: Ensure the UKI business is receiving the correct support from the support partners.
  • Team Development: Line manage, coach, and develop a small team.

8. Survey Data Manager Overview

  • Survey Leadership: Leads the survey data process for the large clinic business.
  • Questionnaire Development: Develops and designs questionnaires.
  • Business Requirements Input: Provides input into business requirements for survey tools and processes.
  • Data Management: Handles data collection, cleaning, analysis, and reporting.
  • Report Production: Produces reports including layout, table and graph generation, writing, proofing, and editing.
  • Client Liaison: Acts as a client liaison, building client relationships and serving as a key point person for questions about survey data and processes, while being proactive in anticipating client needs.
  • Survey Development: Assists with the development of new surveys or metrics.
  • Survey Testing: Tests survey programming, monitors participation, and reporting for custom surveys in Qualtrics.
  • Collaboration: Develops and maintains effective relationships with consulting practice members to collaborate on survey design, content, and reporting to ensure deliverables meet the needs of consultants, participants, and clients.
  • Content Contribution: Contributes to articles and marketing materials for client and prospect distribution and for posting to the SullivanCotter website through detailed research of various data assets.
  • Operational Efficiency: Identifies and implements opportunities for efficiencies in day-to-day survey operations by leveraging software and programming solutions.
  • Data Strategy Development: Develops and delivers a data strategy, roadmap, and project management to drive data insight-led decision-making to underpin and shape the growth of the fundraising strategy.
  • Department Support: Proactively supports the Income Department with timely and accurate data selections, imports, reporting, and analysis in line with user requirements.

9. Benefits and Data Manager Details and Accountabilities

  • Data Landscape Understanding: Understand and document the data landscape and data flows within CPR Biology.
  • Data Stewardship: Serve as the functional data steward.
  • Data Management: Manage good data structure and harmonize data across systems by promoting best practices and processes.
  • Data Quality Improvement: Drive data quality initiatives to improve data reliability and enable its reuse.
  • Benefits Tailoring: Work with internal employees to understand needs and tailor benefits packages to position.
  • Benefits Evaluation: Evaluate how effective the benefit packages are in terms of employee satisfaction.
  • Information Assembly: Assemble information regarding benefits products and data needs.
  • Cost Analysis: Conduct cost analyses before selecting benefits for employees.
  • Data Process Assessment: Assess data processes and undertake data improvement initiatives to ensure employee records are accurate and up to date.
  • Provider Communication: Communicate with benefit providers to ensure services are supplied according to agreement.
  • Trend Identification: Identify trends and implement new practices to deliver fast access to metrics while ensuring engaged and motivated employees.
  • Supporter Journey Planning: Feed into the development of supporter journey planning and execution, providing support and delivering outputs to achieve overall aims.
  • Compliance Assurance: Ensure all data is held and processed in accordance with protocols and GDPR, leading on best practices that meet fundraising and data legislation.

10. Data Manager Tasks

  • Data Governance Support: Supporting the management in the creation of data governance strategy, translating objectives into tactical implementation, execution of processes, tools, and organizational change.
  • Business Opportunity Identification: A proactive approach to identifying new business opportunities and synergies in the area of data analytics.
  • Process Improvement: Looking for new ways to improve existing data processes using actionable opportunities to increase efficiencies and enhance the customer experience.
  • Data Transformation Leadership: Leading data transformation with guidance from the Regional Head of Data Management.
  • Governance Design: Designing and implementing governance surrounding data requests, ensuring consistency in the request intake process and proper ownership.
  • Team Leadership: Leading a team of data professionals both directly and as part of the matrix organization.
  • Technical Guidance: Providing technical guidance to data analysts regarding technologies and tools available for use within CBRE.
  • IT Collaboration: Collaborating with IT leaders to evaluate and provide insight into IT solutions to support the transformation together with IT.
  • Quality Reporting Implementation: Implementing solid quality reporting and analysis to improve data quality.
  • Presentation Preparation: Preparing presentations and performing follow-up activities in support of Data Management Group meetings.
  • Centralized Contact Point: Acting as a primary centralized point of contact.
  • Business Coordination: Coordinating business collaboration across the enterprise.