
Manager, Data Architecture and Engineering, gTech
- Gurgaon, Haryana
- Permanent
- Full-time
- Bachelor's degree or equivalent practical experience.
- 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
- 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks.
- 3 years of experience in a people management, supervision, or team leadership role.
- 7 years of experience developing project plans and delivering projects on time within budget and scope.
- 7 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
- 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, Jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.
- 2 years of experience with Machine Learning for production workflows.
- Experience in implementing and maintaining Data Governance frameworks and processes.
- Partner with cross-functional leaders and teams to determine and prioritize requirements, design Data Engineering solutions that foster analysis and insights and enable our Ads business.
- Lead a team of Product Technology Managers and Data Engineers to synthesize stakeholder requirements and use cases, design data library and develop solutions based on data warehouse, analytics and visualizations.
- Work with leaders to solve strategic and tactical problems around our Ads business by offering data and insights based solutions. Help to scale our engineering capabilities through service providers.
- Lead a team to contribute to designing and iteratively launching data architecture, warehouse, reporting and visualizations that improve strategic and operational decision making.
- Own cross-functional organizational standards to drive clarity and consistency across metric and dimensions and ensure quality and consistency as our Ads business grows. Manage support and product taxonomy.