About Digital Technology:
We’re not yesterday’s IT department, we're Digital Technology. The world around us keeps changing and so do we. We’re redefining what it means to be IT with a mindset centered on transformation, experience, AI-driven automation, innovation, and growth.
We’re all about delivering delightful, secure customer and employee experiences that accelerate ServiceNow’s journey to become the defining enterprise software company of the 21st century. And we love co-creating, using, and highlighting our own products to do it.
Ultimately, we strive to make the world work better for our employees and customers when you work in ServiceNow Digital Technology, you work for them.
ServiceNow is changing the way people work. With a service-orientation toward the activities, tasks and processes that make up day-to-day work life, we help the modern enterprise operate faster and be more scalable than ever before.
As a member of the Data & Analytics team, you’ll focus on driving operational awareness to our Executive Team while partnering with leaders throughout ServiceNow to fundamentally improve how we run our business. With a combination of exceptional analytical skills, an insatiable curiosity, and an entrepreneurial “get stuff done” mindset, you’ll help us better understand our customers, partners, and products, and drive important changes that will shape the future of ServiceNow.
What you get to do in this role:
We are looking for a Rock Star with a winning track record in Big Data, Data Warehousing, Visualization and Data Web Services. The Senior Staff Data Engineer will be a core technical contributor to the team with deep expertise in manipulating and structuring large, complex datasets that feed central data warehouses. S/he will be responsible for helping stand up and maintaining daily data transfer jobs, database structures, identifying data integrity issues, and developing documentation on data assets. The Senior Staff Data Engineer will also work closely with ServiceNow data analysts and data scientists to help prep data for models and dashboards.
The ideal candidate should have a background in Engineering, Statistics, Mathematics, Computer Science, equivalent quantitative field or related practical experience with an obsession on data quality. S/he should have an outstanding ability to foster relationships with staff across departments and be motivated to continuously achieve positive results. Extensive understanding to the needs of data visualization is a must for this role. S/he should also be able to effectively handle ad hoc requests and multitask with ease and little guidance.
Examples Of Day-to-Day Responsibilities:
- Enforcing company data policies and procedures to ensure data quality and reduce discrepancies
- Securing approvals for data access based on business needs
- Developing scalable automated ETL jobs and maintain them
- Identify any data integrity issues and deep dive to find root cause
- Develop and manage Python and API calls to stand up master data sets and merge datasets across disparate systems
- Training analysts and data scientists alike on available data sources
- Ensuring very large databases and compute clusters operate optimally
- Implementing and maintaining database structures and governance
- Developing / maintaining documentation on databases and production tables
- Collaborating across the company’s multiple data teams to meet analytics deliverables