Director of Data Engineering

Gravity IT Resources

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Job Title: Director of Data Engineering

Location: Miami, Florida

Job-Type: Direct Hire

Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).

 
Overview:
The primary mission of the Director of Data and Analytics Engineering role is to help our business evolve into an insights-driven organization. The position sits in our Enterprise Data and Analytics team, which aims to drive improved business outcomes using insights gleaned from data and analytics and infuse them into our clients fabric. The Director of Data and Analytics Engineering will be accountable for all the engineering work required to execute on our data and analytics strategy and roadmap. The leader will direct the development of the enterprise data and data science platforms as well other advanced data and analytics products. The leader will work closely with product owners and analytics resources to define and develop our next-generation data and analytics capabilities.
 
Responsibilities:
Principal Duties and Responsibilities:

  • Lead development of core platforms, products and technologies that support data and analytics
  • Architect a connected set of infrastructure and data to enable rapid development and testing of new data and analytics products and services
  • Build and lead a high-performing machine learning platform team to architect, design, and develop scalable and cost-effective machine learning platform software and services
  • Partner closely with analytics leaders and product owners to create out next-generation data and analytics capabilities
  • Help develop strategy and process framework for the development of advanced analytics and automation to be used across the organization
  • Drive investments in artificial intelligence and machine learning technology to support business goals and outcomes
  • Lead teams of data engineers, full stack data engineers, and machine learning engineers
  • Provide technical leadership in cutting-edge data and analytics engineering systems design and architecture
  • Drive “closed-loop” insights processes using technology to drive action and deliver improved business outcomes
  • Establish DataOps standards and best practices
  • Support data governance process system and data workflow maintenance by documenting metadata, establishing quality measures, validating calculations, remediating issues, and promoting automation
  • Drive continuous improvement through measurement and monitoring
  • Develop and execute on advanced data and analytics product engineering roadmap

 
Qualifications:
Education and Experience Requirements:

  • Masters Degree preferred or multiple certifications in related focuses
  • 12+ years leading data and analytics engineering teams and delivering significant ROI to businesses
  • 6+ years leading the development of data warehouses, data marketplaces, and data science environments
  • 6+ years building advanced analytics products
  • 4+ years managing data science teams
  • Thirst to help transform our client into an insights-driven organization
  • Proven track record of delivering modern data and analytics engineering solutions at scale to help deliver business outcomes through analytics
  • Ability to be hands on and mentor team when needed with code, code review, architecture etc
  • Extensive experience building modern data warehouses and data science platforms
  • Demonstrated ability to deliver end-to-end data products that put information and insights into the hands of the business user
  • Experience working with business users to understand how to optimally deliver insights with their operational workflows and decision-making processes
  • Extensive experience operationalizing data science models and monitoring in production
  • Demonstrated ability to define, develop, and deliver end-to-end data and analytics solutions using a product management lifecycle approach
  • Experience with semantic data modeling and knowledge graphs and engineering
  • Proficiency in data quality measures and understanding of data and analytic governance
  • Successful management of advanced analytics and AI investments
  • Ability to help prioritize experimental data science work based on feasibility and success likelihood
  • Experience deploying intelligent process automation systems
  • Expert in cloud development and automation technologies
  • Ability and willingness to quickly learn new technologies
  • Knowledge of one or more visualization tools such as Tableau or Looker

Physical Requirements:
This is primarily a sedentary office position which requires the incumbent to have the ability to operate computer equipment. Finger dexterity is necessary. Travel up to 10% required.
Additional Requirements:

  • Travel up to 10% of the time
  • Interact well with co-workers
  • May be required to cross train for position(s) within the team organizational structure from time to time, as required by the Leadership Team
  • Comply with and implement company policies and procedures
  • Accept constructive criticism
  • Strong work ethic
  • Team player

 

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