Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.
Your work profile
We are looking for an experienced Tech Lead to drive the design, development, and delivery of our backend systems. In this role you will combine hands-on engineering with technical leadership — setting direction, mentoring engineers, and owning the quality and scalability of the services your team builds.
You will work primarily within a Python ecosystem (Django or Flask), deploy and operate workloads on AWS, and design event-driven data flows using Apache Kafka. Beyond writing code, you will be accountable for architecture decisions, engineering standards, and the growth of the people on your team.
Key skills required:
Lead the technical design and architecture of backend services, APIs, and data pipelines, balancing scalability, reliability, and maintainability.
Own delivery of features end to end — from requirements and design through implementation, code review, testing, deployment, and production support.
Provide hands-on engineering contribution, writing high-quality, well-tested Python code and setting the standard for the team.
Mentor and guide engineers, conducting code reviews, pairing, and supporting career growth and skill development.
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Define and enforce engineering best practices around coding standards, testing, CI/CD, observability, and security.
Collaborate with product managers, designers, and other stakeholders to translate business goals into technical roadmaps.
Design and operate event-driven systems using Kafka for reliable, scalable inter-service communication.
Manage cloud infrastructure and deployments on AWS, optimising for cost, performance, and resilience.
Identify and resolve technical debt, performance bottlenecks, and production incidents.
Preferred Qualifications
Bachelor’s degree in business, Engineering, Management, or a related field
Overall Software Engineering Experience
Breadth: A minimum of 8 years of professional software engineering experience, with a track record of shipping and maintaining production-grade systems.
Depth: Demonstrated progression from individual contributor to a senior or lead-level engineer, with ownership of significant features or systems.
Fundamentals: Strong grounding in software design principles, data structures, algorithms, API design, and system architecture.
Lifecycle: Experience across the full software development lifecycle — requirements, design, implementation, testing, deployment, and maintenance.
Python & Web Frameworks (5+ years, Django or Flask)
Core Python: At least 5 years of hands-on experience building applications in Python, with deep knowledge of the language and its ecosystem.
Frameworks: Production experience with Django or Flask, including building and maintaining RESTful APIs and web services.
Data & ORM: Proficiency with relational databases (e.g. PostgreSQL, MySQL) and ORMs such as Django ORM or SQLAlchemy, including query optimisation.
Quality: Strong testing discipline using frameworks such as pytest or unittest, and experience integrating tests into CI pipelines.
Performance: Experience profiling, debugging, and scaling Python services under real-world load.
Cloud Engineering on AWS (Developer Perspective)
Hands-on: Practical, developer-focused experience building and deploying applications on AWS — not just consuming managed services superficially.
Core services: Working knowledge of services such as EC2, S3, Lambda, RDS, IAM, and API Gateway in the context of application development.
Deployment: Experience packaging and deploying applications using containers (Docker), and familiarity with ECS/EKS or similar.
Operations: Understanding of monitoring, logging, and alerting on AWS (e.g. CloudWatch) to keep services healthy in production.
Best practices: Awareness of security, cost-efficiency, and infrastructure-as-code (e.g. CloudFormation or Terraform) is a strong plus.
Technical Leadership & Team Management (3+ years)
Leadership tenure: A minimum of 3 years leading engineering teams or squads, whether as a tech lead, team lead, or engineering manager.
Mentorship: Proven ability to mentor and grow engineers through code reviews, pairing, and structured feedback.
Delivery ownership: Experience planning, estimating, and delivering projects on time while managing scope and technical trade-offs.
Collaboration: Skilled at working cross-functionally with product, design, and other engineering teams to align on goals and priorities.
Communication: Excellent written and verbal communication, able to explain complex technical concepts to both technical and non-technical audiences.
Event Streaming with Apache Kafka (1+ year)
Practical experience: At least 1 year of hands-on experience working with Apache Kafka in a production or near-production environment.
Producers & consumers: Experience designing and implementing Kafka producers and consumers, including topic and partition design.
Event-driven design: Understanding of event-driven architecture patterns, message ordering, delivery guarantees, and schema management.
Reliability: Familiarity with handling failure scenarios such as retries, dead-letter queues, and consumer lag monitoring.
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