• VP, Data Engineering

    Job Locations 2 months ago(4/13/2018 2:47 PM)
    Requisition ID
    Posted Date
    Advanced Analytics
    32 Avenue of Americas
  • Overview

    Vice President, Data Engineering


    360i is looking for a strong team and technical leader to manage and evolve our cloud data infrastructure, including oversight of the architecture and development of the front end, back end and associated, robust intelligence and reporting systems.


    The VP, Data Engineering will work closely with digitals analysts, marketing scientists and media managers to understand data needs, enable accessibility to the data, and set standards to improve the organization and the scaling of our data applications overall. Experience with AWS operations management is a strong plus

    As a team leader, you should enjoy getting your hands dirty coding, problem solving, mentoring junior and mid-level engineers, and fostering innovative thinking. You will help to drive the right technology choices (e.g. languages, libraries, frameworks), have the opportunity to define how we work as a team, and help to prioritize the products and tools we build.


    You will help architect client and vertical specific solutions by identifying custom needs and determining the best approach to solve via custom client development, platform team prototyping, or core product development. The role is also client facing, working account teams to solve business problems throughout pitches, client implementations, and ongoing platform usage.


    Lead the architecture and the development of data and analytics enterprise applications across the agency


    • Grow our extensive library of Media Partner APIs (DoubleClick, Google, Adobe, Facebook, etc.)
    • Develop and evolving our cloud infrastructure and architecture (using AWS and Google Cloud)


    Collaborate with multi-tiered stakeholders to prioritize, plan and develop solutions across data product suite and across the broader agency, working with both technical and non-technical teams


    • Meet with key internal stakeholders to diagnose client-specific data and delivery requirements
    • Enhance customized ETL processes to efficiently harmonize and standardize data products
    • Construct custom QA Processes to detect data irregularities and construct corrective algorithms

    Define vision, drive team execution, and oversee the architecture and engineering process. This will require strong leadership capabilities, and the ability to ensure alignment across the organization.

    • Mentor and guide the professional and technical development of your team members.
    • Help develop their careers, ensure they progress their skill levels, understand their work styles and apply that understanding toward helping them set and reach professional goals.


    Innovate with and expand the organization's insight, intelligence and analytics products, emerging approaches, skills and technologies.

    • Identify structural and process improvement opportunities, including best practices for modern development principles and methodologies.
    • Research and develop new data solutions and tools sets.
    • Oversee the development and release of an enterprise BI platform.



    • The ideal candidate will have a B.S. degree in Computer Science, Data Science or equivalent. Master’s degree preferred.
    • 10-12 years’ experience in a software development role in Enterprise data applications (i.e. big data, data warehousing, data science, and analytics solutions) including 3+ years in a technology leadership position, digital media experience is preferred.
    • Preferred candidates have an established track record of defining solutions and leading the implementation of large-scale high quality enterprise solutions.
    • Proven ability to assess an existing business process and implement a next generation solution using a services-based approach.
    • Solid understanding and experience in the Agile methodology, hands on management of agile, iterative development spanning specification, prototyping, architecture, QA, operations and support.
    • Technical Requirements
      • SQL databases: PostgreSQL and Microsoft SQL Server
      • Cloud platforms: AWS and Google Cloud
      • Building ETL processes with Python
      • Hadoop data batch processing: Spark and Hive
      • Business productivity tools: Powerpoint, Excel
      • Operations tools: Kanban boards, Git, Jira
      • Data visualization tools: Tableau, Datorama, D3.js, Altair, Plotly
      • Scientific Python libraries such as Pandas, Scikit, Statsmodels
      • Knowledge of marketing data (display, search, social) a plus
      • Data analytics experience a plus (R, SAS, SPSS).


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