Senior Data Engineer

Informa  is a leading academic publishing, business intelligence, knowledge and events business, creating unique content and connectivity for customers all over the world. It is listed on the London Stock Exchange and is a member of the FTSE 100.

Taylor & Francis  is one of the world’s largest publishers of high-quality, peer reviewed scholarly journals, books, e-books and reference works. We empower learners, thinkers and doers with trusted knowledge that advances research and enriches lives. We bring together diverse people, ideas and opinions to validate and publish the experts, theories and truths that matter. And we’ve been doing this in an unbroken arc since 1798.

Our purpose is to foster human progress through knowledge. We strongly believe that this requires us to encourage and examine different ideas and voices, so that any work that meets our exacting levels of quality deserves to be included in our publications. This requires open minds, the opportunity for robust debate, and the courage to defend perspectives that stand up to scrutiny, even if they conflict with our personal beliefs or values. Because that’s the only way to find the best obtainable version of the truth and, ultimately, foster human progress. If you agree, then we’d love to hear from you.

Job Description

We are seeking an experienced Senior Data Engineer to join our Data and Analytics Platform team. In this role, you will collaborate with data quality engineers and business data analysts to understand data requirements and models, build robust data ingestion pipelines, and develop complex business-specific use cases that enable seamless information consumption from our platform. 

You will be part of a dynamic and enthusiastic team driving agile development to build an enterprise-level data analytics platform as part of Taylor & Francis's product and technology-led initiatives. The ideal candidate will possess strong hands-on experience with diverse data management methodologies and a proven track record of implementing them across a wide range of data projects to generate highly relevant data products. 

Building Scalable Data Pipelines  

Design and develop high-quality, scalable ETL/ELT pipelines for processing big data using AWS analytical services. Leverage no-code tools and reusable Python libraries to ensure efficiency, maintainability, and reusability. Ensure data pipelines and platform components are scalable, performant, and cost-efficient. 

Platform Engineering  

Build and enhance reusable platform capabilities across ingestion, transformation, orchestration, data quality, cataloguing, and monitoring. Develop scalable and reliable AWS data pipelines and data products using standardised data architecture patterns such as medallion architecture, lakehouse, and other modern design paradigms. 

Data-Related Automation  

Drive configuration-driven, declarative, and automated engineering approaches that reduce bespoke development and improve productivity. Champion automation across the data engineering lifecycle to minimize manual intervention and accelerate delivery. 

Collaborating & Aligning with Project Goals  

Work closely with cross-functional teams, including Tech Leads, Engineering Managers, and Business Analysts, to understand project objectives and deliver robust data solutions. Follow Agile/Scrum principles to drive consistent progress and iterative delivery. 

Data Discovery & Root Cause Analysis  

Perform data discovery and analysis to uncover data anomalies. Identify and resolve data quality issues through root cause analysis, and provide informed recommendations for data quality improvement and remediation. 

AI-Augmented Development  

Champion the integration of Claude Code and other LLM tools into our software development lifecycle (SDLC). Lead the team in using AI to accelerate coding, debugging, automated testing, and documentation. 

CI/CD & Operational Excellence  

Manage the automated deployment of code and ETL workflows within cloud infrastructure (AWS preferred) using tools such as GitHub Actions, AWS CodePipeline, or other modern CI/CD systems. Implement Infrastructure as Code (IaC), automated testing frameworks, observability solutions, security best practices, and operational reliability measures to ensure robust and resilient data platform operations. 

Effective Time Management  

Demonstrate strong organizational and time management skills. Prioritize tasks effectively and ensure the timely delivery of key project milestones. 

Technical Mentorship  

Set the gold standard for the team by leading code reviews, defining CI/CD patterns, and enforcing data governance standards via AWS Lake Formation. 

The AI Frontier (SageMaker & Bedrock)  

Architect the infrastructure for our AI initiatives. Implement our initial AWS SageMaker footprint (Data Wrangler, Feature Store) and manage AWS Bedrock integrations (Knowledge Bases, RAG pipelines) to support downstream Data Science and GenAI initiatives. 

Documentation & Data Mapping  

Develop and maintain comprehensive data catalogs, including data mapping and documentation, to ensure data governance, transparency, and accessibility for all stakeholders. 

Learning & Contributing to Best Practices  

Continuously improve your skills by learning and implementing data engineering best practices. Stay updated on industry trends and contribute to team knowledge-sharing and codebase optimization. 

What You Will Be Doing (Daily Execution & Process)  

Data Engineering  

Build and evolve reusable data platform capabilities. Develop scalable ingestion, ETL/ELT and data processing solutions using AWS. Implement and support medallion data processing and data product patterns. Build automation around data quality, metadata, cataloguing, orchestration and monitoring.  

Agile Orchestration  

Function as an integral part of an Agile engineering team, defining delivery phases, sub-activities, and milestones while ensuring development standards are rigorously enforced. 

Project Delivery  

Collaborate with Engineering Managers and Business Analysts to produce accurate delivery estimates and oversee the transition from analysis through to final delivery. 

Infrastructure as Code (IaC)  

Create and maintain resilient infrastructure using Terraform or AWS CloudFormation and strong deployment practices enabled by automated tests to ensure environment parity and automation stability . 

Quality & Testing  

Implement comprehensive unit testing strategies and automated data quality checks to identify and resolve issues prior to deployment. 

Observability & Monitoring  

Establish and maintain observability practices including logging, monitoring, and alerting to ensure platform health, performance optimization, and proactive issue detection. 

Cross-Functional Collaboration  

Work closely with cross-functional teams to gather requirements and develop cloud-based applications, analytical services, and platforms. 

Security & Compliance  

Ensure all data solutions strictly adhere to company security guidelines and regulatory requirements. Implement security best practices throughout the data engineering lifecycle. 

Knowledge Management  

Document technical solutions and maintain a robust knowledge base for the team. 

Qualifications

3. Technical Requirements (

Qualifications

Experience  

6+ years in Data Engineering, with deep expertise in architecting scalable cloud-native data solutions, optimizing complex ETL/ELT workflows, and implementing modern data platform patterns including lakehouse and medallion architectures. 

Data Expertise  

Strong analytical skills in handling and processing structured and semi-structured datasets, with hands-on experience in designing and implementing scalable and cost-effective data engineering solutions on AWS. 

Cloud Technologies  

Proficiency in building data pipelines and working with data warehousing solutions on AWS (Redshift, S3, Glue, Lambda, etc.). Experience with alternative cloud platforms (Google Cloud, Azure) is a plus. 

Programming Skills  

Strong programming proficiency in Python, with additional experience in Java/Scala being advantageous. Ability to write efficient, reusable, and scalable code to process large datasets. PySpark experience is a plus. 

Data Warehousing  

Proven experience with modern data warehousing tools such as AWS Redshift, Snowflake, or equivalent platforms, with a focus on performance optimization and query tuning. 

Platform Engineering & Architecture  

Experience building reusable platform capabilities and implementing standardised data architecture patterns including medallion architecture, lakehouse, and modern data mesh principles. 

AI-Enabled Engineering  

Proficiency in using Claude Code or similar AI assistants to streamline complex engineering tasks. 

MLOps  

Familiarity with setting up SageMaker or Bedrock environments to build the infrastructure where models operate. 

Data Modeling  

Advanced knowledge of Star/Snowflake schemas and modern Data Lake design principles. 

Version Control & Automation  

Hands-on experience with version control systems such as GitHub, GitLab, or Bitbucket, and with CI/CD pipelines using tools like GitHub Actions, AWS CodePipeline, or Jenkins to ensure smooth, automated deployments. Strong understanding of Infrastructure as Code principles and automated testing frameworks. 

Observability & Operational Reliability  

Experience implementing observability solutions (CloudWatch, Datadog, Grafana, etc.) and ensuring operational reliability through monitoring, alerting, and incident response practices. 

Data Governance & Security  

Knowledge of data governance practices, compliance standards, and security protocols in a cloud environment. 

Automation & Efficiency  

Demonstrated ability to drive configuration-driven and declarative engineering approaches that reduce manual effort and improve team productivity. 

Optional Skills  

Experience with business intelligence (BI) tools such as Tableau, Power BI, or QuickSight, and exposure to data visualization techniques will be an advantage. 

Education  

Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field. 

Additional Information

You must have the right to work and live in India.

Location:  The successful candidate will be able to utilise our balanced working model. We ask that candidates live within a commutable distance of our Bengaluru office to ensure that as a balanced worker they can make it to our office location to collaborate as required. There is an expectation for a minimum of 3 days per week in-person time.

We believe that great things happen when people connect face-to-face. That's why we work in-person with each other, or with customers and partners, three days a week or more. When you’re not spending time together in one of our offices or other workplaces – like at conference – you get the flexibility and support to work from home or remotely.

What we offer in return: 

• A competitive salary + bonus
• 24 days annual leave
• 4 volunteering days annually
• Day off for your birthday
• Pension contributions
• Medical insurance for self and dependants; life cover and personal accident cover for self
• Seasonal social and charitable events
• Training and development
• Tools and equipment for remote working

Note: This role does not provide any relocation support. 

We want all our candidates to shine in our recruitment process. Please let us know if there is anything we can do to ensure you are able to show us your best self. This could include having the application form in a different format, more time for questions, or anything else – please ask us, we are happy to be flexible! Please contact  View email address on jobs.smartrecruiters.com

Being Yourself at Taylor & Francis:  

If you’re excited about working with Taylor & Francis to foster human progress through knowledge, we invite you to apply even if your existing skills and experience don’t fit every item listed above. At Taylor & Francis, we are at our best and most successful when colleagues can be themselves and make a contribution regardless of their identity or background. As a colleague, you will have the opportunity to further innovate and develop in areas that you are passionate about. Our goal is to empower you with the resources, incentives, and flexibility you need to enjoy success at work and to live a healthy, balanced life. 

Taylor & Francis is proud to be an Equal Opportunity Employer. We believe in and value diversity of people and thought, fostering a supportive and inclusive environment where all colleagues can learn and succeed as their true selves. Taylor & Francis recruits, develops, and retains colleagues without regard to any protected personal characteristics or other non-merit based factor. 

If you have a disability, or face another barrier, and would like to request an adjustment to assist your participation in the hiring process and/or in the advertised position, please contact  View email address on jobs.smartrecruiters.com . Your request will be reviewed and considered in the strictest confidence.

We genuinely care about our colleagues, promoting work-life balance, wellbeing, and flexible working. We believe that the skills and experience you bring to Taylor & Francis are invaluable. We want you to have the opportunity to develop your abilities, and to innovate and develop in areas which you are passionate about. To find out more about our business and the great career opportunities please go to our Careers Site:  

Or better yet check out our LinkedIn ‘Life’ Page, highlighting our accomplishments, employees, and company culture. It’s also a good way of meeting our recruitment team, who will be happy to advise you on your journey here at T&F.