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Data Architect

Date: Feb 18, 2021

Location: Washington, DC, US, 20036

Company: American Chemical Society

Division and Unit Overview

The Washington IT Division of the American Chemical Society provides its members and the worldwide scientific community a comprehensive collection of high-quality information products and services for the practice and advancement of the chemical sciences.  ACS’s members and volunteers are the heart of the organization, and the Society and Administrative Technology (SAT) Department within the Washington IT Division aims to support their professional and academic pursuits by delivering intuitive, high quality, highly available, and secure systems and applications.  We intend to exceed the expectations of our business partners by anticipating, understanding, and validating their business needs; providing useful, cost-effective solutions and support promptly; managing data securely and providing the necessary architecture to use and deliver in effective ways; adhering to established guidelines and standards, and continuously adapting to the evolving environment.

 

Position Summary 

The position reports to the Senior Manager, Data Science & Engineering within the Society & Administrative Technology (SAT) department. This Lead Data Engineer is responsible for leading data management and data engineering efforts, including data ingestion and curation, ETL processes, ad-hoc and management reporting, analytics, dashboard development, and data acquisition from transactional systems.  The Lead Data Engineer works to ensure the data integration platforms and architecture are maintained and services delivered to meet the evolving demands of business functionality and technical platforms landscape.

 

The Data Science and Engineering team works closely with all aspects of the full spectrum of data including analysis, architecture, development, visualization, reporting, and advanced analytics. The Data Scientists, Data Engineers and Architects work to build data pipelines that efficiently and reliably move data across systems, as well as the next generation of data tools (including reports, visualizations, and other analytic tools) to enable users to take full advantage of this data.

 

In this role, the work will broadly influence ACS’s data consumers and analysts. The Principal Data Architect will get the opportunity to work with focused and scaled objectives while working with a variety of rich data sources. In addition, this role will work on data architecture, development, visualization and analytics projects to provide information and insight to enable data driven business decisions that help optimize performance and increase value for ACS constituents.

 

The ideal candidate should be comfortable with operating across the full spectrum of the data space and be comfortable operating as a business and technical analyst bringing a combination of solid analytics and engaging communication abilities to collaborate with colleagues. The ideal candidate should also possess the ability and drive to proactively collect requirements via discussions with customers, develop project specifications, document project requirements, and communicate with all stakeholders involved in development and deployment processes.

 
Position Accountabilities

  1. Lead a team comprising of data engineers and ETL developers (onsite and offshore)
  2. Lead data management activities from a tactical and operational perspective
  3. Oversee and maintain an effective architecture, database administration and ETL development
  4. Lead the evolution of the data platform architecture to encompass data virtualization, big data, data discovery sandboxes, and real time data services
  5. Provision the data analytics infrastructure to support contractual and operational business goals
  6. Work with management to define the strategy and roadmap for the adoption of data projects, including, marketing, analytics, and business intelligence across the enterprise
  7. Delivers data engineering expertise for ingestion and transformation pipelines that handle data for analytical or operational uses across various business needs and enterprise data domains.
  8. Ensures production stability for data processing workflows used by analytics groups and data scientists who are interrogating information for predictive analytics, machine learning, and data mining purposes.
  9. Maintain awareness of new developments and trends in the data integration and data warehousing space and provide oversight and input for maintaining and evolving data model design practices and data integration architecture for the organization.
  10. Perform other duties as assigned

 

Qualifications

  • Bachelor’s degree in Computer Science, Information Systems, Mathematics or similar discipline
  • Technical expertise
    • Experience working with a broad range of modern data science and analytics tools (e.g., SQL, Python, Tableau, ETL tools, and cloud platforms such as AWS)
    • Experience with leading teams and managing technology operations
    • 7+ years of experience programming in SQL (T-SQL, PL/SQL, or other SQL-based database programming languages)
    • 7+ years of experience with defining database structures and integration pipelines
    • 7+ years of experience with data architecture, understanding database schemas, and building data models that enable reporting and analytics 
    • 5+ years of experience with developing canned and custom application reports using tools such as SQL Server Reporting Services
    • One or more years of experience working with Python
    • Ability to identify, analyze, and interpret trends or patterns in complex data sets 
    • Ability to understand the principles of API development
  • Data management expertise
    • 7+ years of experience with data management, including governance, master data management, as well as policies around data standards and acceptable use of data
    • 3+ years of experience with implementing policies and procedures around data governance to ensure best practices of data architecture, including accountability, governance, and requirements
  • Business analysis and soft skills
    • Business Analysis: Ability to quickly transform a conversation into a set of business requirements and transform business requirements  into technical specifications 
    • Quality Assurance and Operations: Manage the quality assurance and operations for the business intelligence and data products that are already released as well as developed 
    • Collaboration: Ability to build partnerships with cross‐functional teams to develop a comprehensive understanding of key data drivers and opportunities within the business
    • Effective Communication: Ability to communicate findings from data analysis and visualization and present information clearly and succinctly, and identify the analytic needs for departments to enable business results. Departments will include but not be limited to Membership, Marketing, Society Business Solutions, Education, and Information Technology
    • Drives Results: Uncover, gather, compile, and deliver insightful, value‐added business analyses and findings to senior management and their teams while fostering an environment of accountability for results. 
    • Project Management: Support  the  creation of  high‐quality  and actionable  data products suitable  for delivery  to  management and team members 
    • Action-Oriented: Derive insights from transactional data 
    • Manage Ambiguity: Operate effectively, even when things are not certain, or the way forward is not clear Strong written and verbal communication skills

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