Staff Data Engineer at ServiceNow

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

0.0

Posted On

05 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Big Data Technologies, Real-Time Streaming, Data Architecture, Data Engineering, Observability Systems, Data Quality, Programming, Automation, Cloud-Native Data Services, ETL Design, Data Modeling, Performance Tuning, AI/ML Concepts, Cross-Team Collaboration, Mentorship

Industry

Software Development

Description

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 — ServiceNow 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 We are looking for a Staff Data Engineer with deep expertise in Big Data technologies, observability systems, and real-time data streaming frameworks to drive the design and scalability of our next-generation data infrastructure. The ideal candidate will be a hands-on technologist who can architect high-throughput data pipelines, ensure observability and performance, and mentor teams on data engineering best practices. This role combines technical leadership, system design, and innovation in building data-driven and observable platforms that support analytics, monitoring, and AI initiatives across the organization. What you get to do in this role: Data Architecture & Engineering: Design, develop, and optimize large-scale data pipelines to support high-volume, low-latency data processing. Real-Time Streaming: Build and maintain real-time data pipelines using Apache Spark (Structured Streaming), Apache Flink, and Apache Kafka for data ingestion and event-driven processing. Big Data Platforms: Work with modern Big Data ecosystems such as Hadoop, Hive, HBase, Delta Lake, Iceberg, or Databricks for large-scale data management and analytics. Observability & Telemetry: Design data collection and processing workflows for logs, metrics, and traces from observability systems like Prometheus, Grafana, Splunk, Elastic, or OpenTelemetry. Performance & Scalability: Ensure data systems are optimized for scalability, resilience, and cost efficiency under large and diverse workloads. Data Quality & Governance: Implement data validation, schema governance, and metadata management across the data lifecycle. Programming & Automation: Develop robust, reusable code and automation using Python, Java, Scala, or Go to enhance reliability and maintainability. Cross-Team Collaboration: Partner with platform, AI, and analytics teams to design data models and streaming architectures supporting predictive and real-time insights. Innovation: Explore and prototype AI/ML-driven observability or anomaly detection capabilities to enhance platform intelligence. Mentorship: Guide junior engineers in best practices for data architecture, streaming, and observability. Qualifications To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 10+ years of professional experience in data engineering, distributed systems, or large-scale data processing. Hands-on experience with real-time streaming frameworks such as Apache Spark (Structured Streaming), Apache Flink, and Apache Kafka. Hands-on experience with one programming language – Java, Python, or Scala. Proven background in Big Data technologies (HDFS, Hive, Impala similar). Strong understanding of observability data (logs, metrics, traces) and integration with monitoring platforms such as Prometheus, Grafana, or Splunk. Experience with cloud-native data services (AWS, Azure, or GCP) for data storage, streaming, and orchestration. Solid knowledge of ETL design, data modeling, and performance tuning. Familiarity with schema governance, data quality frameworks, and CI/CD for data workflows. Good to have: Exposure to AI/ML concepts, particularly anomaly detection, predictive analytics, or intelligent observability. Strong communication and leadership skills with a track record of influencing cross-functional teams. FD21 Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

Responsibilities

Design, develop, and optimize large-scale data pipelines to support high-volume, low-latency data processing. Build and maintain real-time data pipelines and ensure observability and performance across the organization's data infrastructure.