Company Description
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — Service Now stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.
Job Description
In this role, you will be a member of a team that supports analytics for global infrastructure and cloud operations. You will help drive Cloud and Infrastructure strategy by leveraging AI, Machine Learning, and other advanced Analytics to inform our future enterprise strategies.
The work will require ingenuity, vision, and the capability to cultivate strong partnerships across various departments as you develop pipelines, SOT data solutions, and data products foundational to our Cloud and Infrastructure analytics strategy. What you get to do in this role:
Ingest and curate business-relevant structured and unstructured datasets from multiple data sources.
Lead pipeline, development, and maintenance of data models for efficient data storage and extraction.
Provide SME guidance and technical recommendations for data ingestion and management framework.
Leverage algorithms to transform relevant data into actionable information.
Create data validation methods that enforce and follow all company policies and procedures to ensure data integrity.
Automate data management, validation, and ETL tasks via data pipelines.
Lead data engineering projects to extract, manage, and analyze data from multiple applications, ensuring deadlines are met.
Act as a liaison between Cloud Capacity Engineering, data governance, data analytics, and Big Data engineering teams.
Independently Identify business opportunities, capabilities, and solutions that deliver customer satisfaction.
Define and implement critical KPIs and build “operational” dashboards to help teams drive operational rigor and manage performance.
Deliver reliable and coherent data models for organizational-wide dashboards, including forecasting, planning, deployment, incident, problem management, and change management analytics across Cloud/Infrastructure and operations.
Onboard and manage analytics development workspaces and environments,
Solve and present solutions to complex problems in an understandable way to stakeholders, business leaders, and executives.
Remain engaged and involved with industry best practices and policies.
Qualifications To be successful in this role you have:
Bachelors in computer science, data science, Management Information Systems, mathematics, or a related field. An equivalent of the same in working experience is also acceptable for the position.
3+ years of experience as a Data Engineer with advanced knowledge working with a wide variety of RDMS systems featuring SQL, No SQL, HDFS, Scala, Spark, Kafka, R, Git, and related languages to develop, automate, and manage data applications, transformations, and data pipelines at scale.
3+ years of demonstrated Python and SQL development experience is a must.
2+ years of demonstrated proficiency in OOP languages and server-side programming such as Java Script and Java
2+ years’ experience working with Apache Hadoop, Snowflake, and HDFS Cloudera technology stacks.
3 years of working with infrastructure or cloud infrastructure, SASS, IAAS, Fin Tech, capacity planning, supply chain, or data analytics environments.
Demonstrated success working in fast-paced Agile, SDE environments and adaptability to changing requirements.
Knowledge of Tableau, Tableau Prep, Power BI, and other BI analytics tools.