Staff Data Engineer

Staff Data Engineer

This job is no longer open

To complement our rapid growth, we are currently sourcing for a Staff Data Engineer to join our Product Engineering team as a part of the Aceyus team. As a key member of the Product Engineering - Aceyus team, you will drive various initiatives by transforming operational data into valuable business insights, design and maintain stock Aceyus reports and dashboards, and shape our projects to deliver maximum impact. This position is open to qualified applicants nationwide. Candidates residing within 50 miles of our San Ramon, CA or San Francisco, CA offices are required to be in the office three days a week (Mondays, Wednesdays, Thursdays).


  • Work with key stakeholders to design, create, and develop report/dashboard visualization and data element standards across multiple product offerings.
  • Develop and maintain user guides for data warehouse best practices and available data elements across all key datasources.
  • Work with the technical teams to standardize visualization controls within the Aceyus application to support ‘ease of use’ functions for all users.
  • Work with customers and partners to develop corporate branded visualizations, layouts, reports, and dashboard offerings.
  • Work with both sales and technical teams to understand the ‘why’ behind customer requirements to help tell the story or context behind the data itself.
  • Partner with technical teams to influence UI/UX within the Aceyus application and help shape the visual aspects of the product moving forward.
  • Research industry trends for data visualization, KPIs, and other complex analytic solutions designed to help present data to key people within an organization to provide insights and ultimately take action, particularly on the data portion.
  • Ability to work across multiple facets of a project and juggle multiple tasks at the same time.

Required Skills:

  • 5+ years of experience in data analysis role.
  • BS/MS in STEM or quantitative field (CS, Applied Statistics, Operations Research) or BS/MBA in Finance, Accounting, Economics, Business Analytics
  • Familiarity with a variety of data visualization techniques and libraries.
  • Experience working in a fast-paced agile environment.
  • Experience working with enterprise systems and understanding of data design pattern differences between transactional systems and analytical data warehouses.
  • Experience with data analytics tools and languages (R, Python).
  • Experience with commercial and emerging BI databases, technologies, and languages.
  • Knowledge of accounting principles, financial statements, and financial modeling.
  • Excellent problem-framing, problem solving and project mgmt. skills and ability to change direction quickly.
  • Experience with git and version control workflows.
  • Attention to detail and personal pride in work undertaken.
  • Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity
  • Strong communication skills, and ability to work with multiple stakeholders.
  • Create clean, reliable, and scalable “single-source-of-truth” data sets by partnering with business owners and engineering teams to address data issues in upstream systems.
  • Perform data profiling on large, complex data sets and provide insights into data quality challenges.
  • Build, maintain, and improve data models, dashboards, and data pipelines
  • Expert in building, deploying, and maintaining data pipelines using open-source tools (i.e, Airflow, Composer, DataProc, DataFlow)
  • Work with business and engineering teams to drive the development of company’s data, reporting, and analytics platforms
  • Skilled at writing optimized ETL jobs to feed data into BigData systems (i.e., BigQuery, DOMO, Hadoop)
  • Expert in data analysis, visualization, and communication.
  • Experience creating dashboards/visualizations using Data Studio, Looker, Tableau (or similar).
  • Proficiency with t-SQL, postgresql, or any other database scripting language.


This job is no longer open
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