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Senior Data Engineer

Bengaluru, Karnataka, India

Live, first seen by us 85 days ago
Pay
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Work setting
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Work setup in the employer’s posting: On-site
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
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Before you apply

Work authorization
Must already have the right to work in IndiaYou must have the right to work and live in India

What you’ll work on

Full posting
  • Design and develop scalable ETL/ELT pipelines for big data on AWS

  • Build reusable platform capabilities for ingestion, transformation, and data quality

  • Find and fix data quality issues through root cause analysis

  • Manage automated deployment of code and ETL workflows via CI/CD

  • Implement the initial AWS SageMaker setup and Bedrock integrations

From the employer’s posting
Design and develop high-quality, scalable ETL/ELT pipelines for processing big data using AWS analytical services.
Build and enhance reusable platform capabilities across ingestion, transformation, orchestration, data quality, cataloguing, and monitoring.
Identify and resolve data quality issues through root cause analysis
Manage the automated deployment of code and ETL workflows within cloud infrastructure
Implement our initial AWS SageMaker footprint (Data Wrangler, Feature Store) and manage AWS Bedrock integrations

What you’ll bring

All qualifications

Core experience

  • Strong hands-on experience with data management methodologies
  • Experience with AWS analytical services for data pipelines

Preferred experience

  • Experience with alternative cloud platforms (Google Cloud, Azure) is a plus.
Qualification wording
The ideal candidate will possess strong hands-on experience with diverse data management methodologies
Design and develop high-quality, scalable ETL/ELT pipelines for processing big data using AWS analytical services.
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.
Education & alternatives
Education Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field. Additional Information
Apply at Informa Group

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Status in our records
Live
First seen by us
Aug 11, 202685 days ago
Recorded sightings
426
Last seen by us
Nov 4, 2026

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How this job compares

Time since we first saw it

Day 85

Up longer than most. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Informa Group is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 25% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • Scala
  • AWS
  • Azure
  • Datadog
  • Grafana
  • Power BI
  • Redshift
  • S3
  • SageMaker
  • Snowflake
  • Tableau
  • Terraform
  • PySpark
  • GCP
Where the posting names them
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
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
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
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
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)
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
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
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 automationstability. Quality & Testing
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
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
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
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
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
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
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.
MLOps Familiarity with setting up SageMaker or Bedrock environments to build the infrastructure where models operate. Data Modeling

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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 automationstability. 

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 recruitment@tandf.co.uk  

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 recruitment@tandf.co.uk. 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: http://www.taylorandfrancisgroup.com/careers 

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. 

Company Description

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.

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Location & working pattern

Bengaluru, Karnataka, India

- Training and development - Tools and equipment for remote working Note: This role does not provide any relocation support.
Work authorization
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.

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