Gartner Specialist Data Engineer Jobs 2026 | Apply Online
Gartner is inviting applications for the Specialist, Data Engineer position in Gurgaon, India. This opportunity is relevant to candidates with a Master’s degree in Computer Science, Data Science, Statistics, Software Engineering, Information Systems, or a related quantitative discipline. Candidates with 0–2 years of professional experience in data engineering, data management, analytics, software engineering, or related fields involving data integration, transformation, and quality can review the official job requirements and apply.
This role offers an opportunity to work with modern data engineering technologies and AI-ready data products. Candidates can gain practical exposure to Python, SQL, data pipelines, data quality, and analytical platforms while collaborating with research, product, and data science teams. For applicants interested in building a career in data engineering and AI-enabled analytics, this position provides exposure to production-grade systems and scalable data solutions.
Gartner Specialist Data Engineer Jobs 2026: Quick Overview
| Company | Gartner |
| Job Role | Specialist, Data Engineer |
| Qualification | Master’s degree in Computer Science, Data Science, Statistics, Software Engineering, Information Systems, or a related quantitative discipline |
| Experience | 0–2 years |
| Eligible Batches | 2024, 2025, 2026 (subject to qualification and experience requirements) |
| Salary | As per company standards; see salary insights below |
| Job Type | Full-time |
| Job Location | Gurgaon, Haryana, India |
| Department | Tech Market Economics – Data Engineering |
| Job Requisition ID | 114332 |
| Work Mode | Confirm the arrangement on the official application page |
About the Specialist, Data Engineer Role
As a Specialist in Gartner’s Tech Market Economics Data Engineering team, the selected candidate will help build, develop, test, deploy, and operate scalable data pipelines, services, and AI-ready data products. The role supports Gartner’s quantitative research capabilities by transforming data from different sources into reliable, usable resources for analytics, research, and business decision-making.
The position involves working with databases, APIs, analytical platforms, third-party systems, and modern data engineering technologies. The engineer will collaborate with product, research, economics, and data science teams to turn prototypes and business requirements into production-ready solutions. The work also involves improving data quality, governance, validation, documentation, automation, and the reliability of production data platforms.
Key Responsibilities
- Develop, test, deploy, and operate scalable, production-grade data pipelines and AI-ready data products.
- Translate prototype models into enterprise-scale solutions using reusable code and sound engineering practices.
- Collaborate with Product, Data Science, Economic Modelling, Research, and other relevant teams to productionize analytical capabilities.
- Integrate data from internal and external sources, including databases, APIs, analytical platforms, and third-party systems.
- Implement automated data quality frameworks, validation processes, and controls for analytics, AI, and research applications.
- Maintain and improve production data platforms by identifying bottlenecks, strengthening resilience, and expanding automation.
- Establish and promote data standards, metadata practices, naming conventions, and data classification frameworks.
- Design engineering solutions that support Gartner’s analytical platforms and broader data and AI ecosystem.
- Work with researchers, economists, and data scientists to contextualize, visualize, and communicate data for better understanding and decision-making.
Required Qualifications, Skills and Eligibility
- Education: A Master’s degree in Computer Science, Data Science, Statistics, Software Engineering, Information Systems, or a related quantitative discipline.
- Experience: 0–2 years of professional experience in data engineering, data management, analytics, software engineering, or related disciplines involving data integration, transformation, and quality.
- Python: Strong Python programming skills and experience developing data pipelines, analytical workflows, or automation solutions.
- SQL and data technologies: Knowledge of SQL and modern data engineering technologies.
- Data integration: Familiarity with ETL/ELT tools for data integration and workflow automation.
- Data platforms: Experience building, maintaining, or supporting data platforms, databases, pipelines, or analytical systems that use data from multiple sources.
- APIs and data extraction: Experience with APIs, web scraping technologies, and data extraction tools is relevant.
- Cloud and analytics: Exposure to cloud, analytics, or AI-enabled data platforms such as Databricks, Snowflake, or similar technologies.
- Engineering practices: Understanding of testing, code quality, documentation, version control, and reusable component design.
- Data governance: A strong understanding of data quality, data governance, and scalable engineering practices.
- Analytical thinking: Ability to investigate data-related problems and develop scalable analytical solutions.
- Communication: Ability to translate technical concepts and business problems into solutions understandable to technical and non-technical stakeholders.
- Collaboration: Willingness to work with cross-functional teams and contribute to shared engineering goals.
Salary Insights
Gartner has not publicly specified the salary for this particular vacancy in the available job information. An external job listing provides an estimated range of approximately ₹8.5 lakh to ₹14 lakh per annum, but this is a third-party estimate, not an official Gartner salary announcement. Actual compensation may vary depending on qualifications, relevant experience, interview performance, and the company’s compensation structure. Candidates should confirm the final package with Gartner’s recruitment team.
Why Consider This Data Engineering Opportunity?
This role can help candidates develop transferable skills in programming, data integration, analytical problem-solving, data quality, and production engineering. Working with research and data science teams can also provide exposure to how enterprise data supports AI-enabled products and business decisions. With relevant experience, professionals may explore future opportunities in data engineering, analytics engineering, cloud data platforms, data architecture, and AI data infrastructure. Career progression will depend on individual performance, technical depth, and experience.
Recommended Skills and Learning Resources
Candidates preparing for this role should prioritize Python programming, SQL queries, data transformation, and database fundamentals. Understanding ETL/ELT workflows and modern data platforms can also strengthen practical knowledge. The following resources can help build a foundation:
- Python Course and Notes – Review programming fundamentals, functions, data structures, and practical coding.
- SQL Course and Notes – Practise queries, joins, aggregations, and database concepts.
- Complete Data Science Course – Explore data analysis and concepts relevant to data-driven applications.
Interview Preparation
Prepare to explain your Python projects, SQL queries, data processing workflows, and approach to data validation. Practise describing how you would integrate data from multiple sources, identify quality issues, and design reusable code. Review SQL interview questions and answers and revise the fundamentals of databases, programming, testing, and version control. Be ready to discuss your own projects clearly and explain the decisions behind your solutions.
Explore Related Opportunities
- Explore the latest private-sector and IT jobs
- Find internships and practical learning opportunities
- Explore government job notifications
How to Apply for Gartner Specialist Data Engineer Jobs 2026
- Click the Apply Now button below to open Gartner’s official job listing.
- Review the Specialist, Data Engineer job description, qualifications, experience requirements, and location.
- Confirm that your Master’s degree and professional experience meet the stated eligibility criteria.
- Prepare an updated resume highlighting relevant Python, SQL, data pipeline, database, and analytics projects or experience.
- Follow the instructions on Gartner’s official careers portal and provide the requested application details.
- Review your information carefully and submit the application through the official portal.
- Monitor your email and the application portal for any recruitment updates or further instructions.
Application note: The vacancy is listed under requisition ID 114332. Check the official portal for current availability and the latest application instructions before applying.
Frequently Asked Questions
1. Who is eligible for Gartner Specialist Data Engineer Jobs 2026?
Candidates need a Master’s degree in Computer Science, Data Science, Statistics, Software Engineering, Information Systems, or a related quantitative discipline. The listed experience requirement is 0–2 years in data engineering or a related field. Candidates from the 2024, 2025, and 2026 batches should verify that their qualifications and experience satisfy the official criteria.
2. What is the salary for the Specialist, Data Engineer role at Gartner?
The official salary has not been specified in the available job details. A third-party listing estimates approximately ₹8.5 lakh to ₹14 lakh per annum; this is not an employer-confirmed figure. The final compensation should be verified with Gartner.
3. Where is the job located, and what is the work mode?
The position is based in Gurgaon, Haryana, India, and is listed as a full-time role. The precise work arrangement should be confirmed on the official application page or with the recruitment team.
Final Words
If you meet the educational and experience requirements, review the official job description and submit your application with an accurate, skills-focused resume. Strengthen your Python and SQL knowledge, practise data engineering problems, and prepare to discuss your projects confidently. You can also explore related job openings and internships on The Power Hunt to discover other opportunities aligned with your career goals. Visit regularly for more job updates, learning resources, and interview preparation guides.