About Appier
Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
About the role
Appier is looking for a Data Engineering Lead to guide the development of large-scale, best in class data products and foundations. Your teams (managers and senior IC’s) will work across multiple business departments and be responsible for stewarding data from end-to-end. You will be partnering with Solution, Machine Learning, and Product pillars to create a bold vision and roadmap to unleash the value of data across the Appier ecosystem.
Responsibilities
- Work with tech leaders to design/build right architectural patterns, ETL frameworks, data governance, and data warehouse practices to set strategic direction for data engineering at Appier
- Work with upstream data producers, product managers, and business stakeholders to collect right data and build foundational data models
- Own vision for data warehouse and BI tools to build self service reporting infrastructure at Appier
- Own data reliability workstream to improve data quality and reliability of data pipelines and data products
- Establish best practices to improve data architecture, development process and data reliability
- Conduct yearly and quarterly planning to establish long term and short term goals for data teams
- Hire top talent to grow and nurture data engineering teams
About you
[Minimum qualifications]
- 10+ years experience working in software development or data engineering
- 5+ years of management experience with hiring and growing large sustainable teams, managing through senior leaders/managers
- Exceptional communication and leadership skills, with a proven ability to operate in a fast moving environment
- Hands-on approach to closing gaps in data foundations and technical execution, reinforcing development standards and best practices that guarantee high quality, trustworthy data
- Strong understanding of data related security and governance/controls
- Prior experience with Data Warehouse and Data Lake solutions, Could environments, Big Data solutions, and Realtime Streaming solutions
- Knowledge of advanced visualization tools
