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Title: Senior Data Analytics Engineer (GJC 6) Department: Academic Sales Operations Location: Sector - 62, Noida, India Division: Academic Salary: Nil Job Category: Technology About the RoleOxford University Press is looking for a Senior Data Analytics Engineer to play a critical role in enabling high-quality, trusted, and governed data across our Academic division. This is an excellent opportunity for an experienced data professional who enjoys solving complex data challenges, working with multiple stakeholders, and building scalable data solutions that drive business decisions. In this role, you will be the technical expert for Academic data sources and will have the opportunity to shape and maintain certified data workflows that support reporting, analytics, automation, and customer-facing services. You will work closely with data analysts, data engineers, business stakeholders, and enterprise data teams, giving you exposure to a broad range of business and technical initiatives. This role offers the chance to work with modern data engineering practices, including ETL processes, data modelling, workflow automation, and programming languages such as SQL, Python, and R. You will also contribute to improving data quality, governance, and accessibility across Academic, while helping drive standardisation and best practices within the wider Data Analytics team. As the Senior Data Analytics Engineer, you will be responsible for producing clean, accurate, and timely datasets for Academic. You will collaborate with cross-functional teams to understand business requirements, define analytical and operational objectives, and deliver data solutions that support business needs. Key responsibilities include:Interacting with data analysts and business stakeholders to understand requirements and deliver datasets needed for analysis.Collaborating with group data functions to understand OUP s wider data architecture and roadmap, identifying future opportunities and risks.Supporting the Academic Data Analytics team in troubleshooting data quality issues and coordinating resolution with relevant stakeholders.Driving the rollout of Alteryx Server and managing the server environment on behalf of the team.Compiling, maintaining, and governing a suite of approved data workflows.Performing data modelling, transformation, and ETL processes across core data sources to support analytics and operational use cases.Integrating data from multiple systems into unified datasets using SQL, Python, R, or similar technologies.Identifying opportunities to improve processes and streamline data delivery.Supporting the Lead Data Analytics Engineer and Principal Data Engineer in standardising the integration of legacy and disparate systems.Validating data integrity, identifying anomalies, and implementing quality assurance measures to ensure data accuracy.Maintaining thorough documentation of data assets, workflows, and processes.Ensuring adherence to data governance standards and best practices.Mentoring Data Analytics Engineers on workflow management, tooling standards, and engineering best practices.Impact of the roleThe role is critical in establishing and maintaining core aggregated data sources that enable Academic analytics, reporting, automation, and customer-facing services. You will help deliver certified and governed data workflows, improve data accessibility and quality, support strategic decision-making, and strengthen data governance across the Academic division. Success in this role will be demonstrated through:Creation of core aggregated data sources for Academic analysis and automation.Delivery of certified data workflows that support governed reporting and analytics.Effective management of multiple projects and priorities while meeting agreed timelines.Strong collaboration with stakeholders to ensure outputs meet business requirements.Clear, accurate, and comprehensive documentation.Essential CriteriaProficiency in SQL and programming languages such as Python and R.Strong numerical and analytical skills with experience developing and maintaining complex data structures.Proven ability to conduct root cause analysis and troubleshoot data and data-related processes.Strong problem-solving capability and excellent attention to detail.Ability to work collaboratively across cross-functional teams and manage multiple projects simultaneously.Excellent written and verbal communication skills, including the ability to explain complex concepts to non-technical stakeholders.Experience using Git-based workflows, including branching, pull requests, and code reviews, to manage data pipelines, infrastructure, and transformation logic.Desirable CriteriaExperience working with data governance policies and compliance requirements, including GDPR.Experience with BI and workflow automation tools such as Alteryx Designer, Alteryx Server, or similar platforms.SalaryDependent on skills and experience .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.