About the Role:

Location: India / Remote
Experience: Senior-level / Extensive hands-on data engineering experience
Employment Type: Full-time
Role Type: Client-facing Consulting

We are looking for an experienced Staff Data Engineer to play a key role in building and evolving a real-time customer decisioning platform for a leading UK telecommunications group.

The platform determines which offer, message or next-best action each customer receives across three consumer brands and multiple customer channels. It is powered by a sophisticated data ecosystem comprising real-time pipelines, event and feature stores, and data products that support machine learning and customer decisioning.

This is a senior, hands-on engineering role that combines technical leadership, solution design and delivery. You will translate business challenges, such as customer churn prediction, propensity to buy and next-best-action recommendations, into production-ready data products.

You will own solutions end to end – from understanding business requirements and designing the data approach to coding, testing, deployment and ongoing optimisation.

This is also a client-facing consulting position. You will engage confidently with senior client stakeholders, influence technical direction, provide strategic data advisory and contribute to identifying and shaping new business opportunities.

Key Responsibilities:

1. Data Engineering & Solution Delivery

- Translate business requirements, including churn prediction, customer propensity and recommendation use cases, into scalable data products and actionable signals for machine learning and decisioning platforms.
- Design, develop, test and deploy data frameworks, pipelines and data products using Python and other relevant technologies.
- Build and manage event-driven, streaming and batch data pipelines, including complex joins and transformations.
- Develop low-latency data processing capabilities using technologies such as Kafka, Spark and cloud-native data services.
- Own the end-to-end lifecycle of data products, from solution design through production deployment and ongoing optimisation.

2. Data Architecture & Platform Engineering

- Define and evolve the technical direction and data architecture supporting the customer decisioning platform.
- Work with event stores, feature stores and real-time feature-serving platforms to ensure reliable data availability for machine learning and decisioning.
- Establish data contracts, schemas, ownership models, service levels and documentation in collaboration with data science, BI and engineering teams.
- Apply data mesh and federated governance principles to enable scalable and well-managed data products.
- Contribute to the migration and modernisation of data workloads from AWS to GCP.
- Document key architectural decisions through Architecture Decision Records (ADRs).

3. Data Quality, Governance & Security

- Understand how customer events and signals are generated at source and collaborate with source-system teams to address data quality issues at their origin.
- Establish appropriate data quality checks,



monitoring and validation frameworks.
- Ensure data products are well-governed, documented and accessible to authorised consumers.
- Implement appropriate data access controls, data minimisation and retention practices.
- Ensure compliance with UK GDPR and relevant customer data protection requirements.

4. AI-Enabled Engineering & Innovation

- Actively leverage AI assistants and agents throughout the engineering lifecycle, including solution design, coding, testing, data validation and documentation.
- Explore and implement approaches to make enterprise data products AI-ready and agent-accessible through governed datasets, tools and interfaces such as MCP (Model Context Protocol).
- Apply vector databases, retrieval techniques and other relevant technologies to support AI-driven use cases.
- Ensure human oversight and appropriate security controls for AI-generated outputs and production changes.
- Maintain strict controls around customer data, ensuring it is not shared with AI tools unless explicitly approved.

5. Client Engagement & Consulting

- Work directly with senior client stakeholders to understand business challenges and recommend appropriate data solutions.
- Provide strategic guidance on data platforms, data quality, governance and AI readiness.
- Communicate complex technical concepts and recommendations clearly to both technical and non-technical stakeholders.
- Demonstrate sound commercial and business judgement when evaluating solutions and delivery approaches.
- Support the account and consulting teams in developing proposals, estimates and solution approaches for new opportunities.

6. Technical Leadership & Team Development

- Act as the senior technical authority for data engineering around the platform.
- Lead by example through hands-on engineering, technical problem-solving and high-quality delivery.
- Mentor and develop data engineers across UK, nearshore and offshore teams.
- Establish engineering standards, best practices and reusable frameworks.
- Help scale the data engineering capability as the engagement and team grow.

Required Skills & Experience

We are looking for candidates with a strong combination of hands-on engineering expertise, technical leadership and consulting experience.

Core Technical Skills

- Extensive experience in data engineering, building and operating large-scale data platforms.
- Solid programming experience in Python.
- Hands-on experience with streaming and batch data processing frameworks, particularly Apache Kafka and Apache Spark.
- Experience with cloud data platforms such as Google BigQuery, Snowflake or Databricks.
- Experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions.




- Positive understanding of cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD and production monitoring.
- Experience building and managing event-driven data pipelines and real-time data processing systems.

Data Architecture & Advanced Data Concepts

- Practical experience with feature stores and real-time feature serving.
- Solid understanding of data mesh, data contracts and federated data governance.
- Experience developing reusable data products with defined schemas, ownership, SLAs and documentation.
- Understanding of vector databases, retrieval architectures and AI-enabled data use cases.
- Experience with modern data transformation and modelling tools such as dbt.

Domain & Business Experience

- Experience working with customer data in telecommunications, retail or financial services.
- Exposure to customer analytics use cases such as churn prediction, propensity modelling, recommendations and next-best-action decisioning.
- Understanding of how customer data and behavioural events are generated, processed and consumed across enterprise platforms.
- Practical knowledge of UK GDPR and data protection requirements.

Consulting & Leadership Experience

- Experience in a client-facing consulting or professional services environment.
- Confidence in engaging with senior business and technology stakeholders.
- Experience in technical leadership, mentoring and guiding distributed engineering teams.
- Exposure to pre-sales activities, proposal development, estimation and solution shaping.
- Ability to balance technical excellence with commercial considerations and business outcomes.

Desirable Skills & Experience

- Experience with cloud platform migration, particularly AWS to GCP.
- Experience building AI-ready and agent-accessible data platforms.
- Familiarity with MCP and other approaches for securely exposing enterprise data to AI agents.
- Experience with vector databases and retrieval-augmented generation (RAG) architectures.
- Relevant cloud, data engineering or architecture certifications.

Note: Certifications are welcome but not mandatory. We place greater emphasis on practical experience, demonstrated technical capability and successful delivery of complex data engineering solutions.

What Makes This Role Interesting?

- Work on a high-impact, real-time customer decisioning platform for a leading UK telecommunications group.
- Solve complex data engineering challenges involving large-scale customer data, streaming pipelines and machine learning.
- Influence the technical direction and evolution of a strategic data platform.
- Work at the intersection of data engineering, cloud modernisation and AI innovation.
- Take ownership of end-to-end engineering delivery while engaging directly with senior client stakeholders.
- Play a key role in building and growing a distributed, high-performing data engineering team.

Pay: ₹510,000.00 - ₹1,880,000.00 per year

Benefits:

- Flexible schedule
- Paid sick time
- Paid time off
- Provident Fund

Work Location: Remote

📌 Sr. Data Engineer (India)
🏢 Process360
📍 India