Lead, Platform Engineering

2 mesi fa

Milano, Italia Bain & Company Inc A tempo pieno

**WHAT MAKES US A GREAT PLACE TO WORK**

We are proud to be consistently recognized as one of the world’s best places to work, a champion of diversity and a model of social responsibility. We are currently #1 ranked consulting firm on Glassdoor’s Best Places to Work list and have maintained a spot in the top four on Glassdoor’s list for the last 13 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents.

**WHO YOU’LL WORK WITH**

As a member of Bain's Advanced Analytics Group (AAG) you’ll join a talented team of diverse and inclusive analytic and engineering professionals who are dedicated to solving complex challenges for our clients. We work closely with our generalist consultants and clients to develop data-driven strategies and innovative solutions. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

**WHERE YOU’LL FIT WITHIN THE TEAM**

As a Lead, Platform Engineering you will design and build cloud-based distributed systems that solve complex business challenges for some of the world’s largest companies. You will draw on your deep software engineering, cloud engineering, and DevOps expertise to design and build technology stacks and platform components that enable cross functional AI Engineering teams to create robust, observable and scalable solutions.

**WHAT YOU’LL DO**:

- Cloud solution and distributed systems architecture for full stack AI software and data solutions
- Collaborate closely with and influence general consulting teams to develop analytics solutions to client business problems, to prioritize and execute those solutions
- Defining and implementing scalable, observable, manageable, and self-healing cloud-based solutions across AWS, Google Cloud and Azure
- Implementation, testing and management of Infrastructure as Code (IAC) of cloud-based solutions that may include CI/CD, data integrations, APIs, web and mobile apps, and AI solutions
- Participate in code reviews and contribute to the establishment and enforcement of coding standards and best practices to ensure high-quality, maintainable code
- Develop and maintain APIs and microservices to expose analytics functionality to internal and external consumers, adhering to best practices for API design and documentation
- Implement robust security measures to protect sensitive data and ensure compliance with data privacy regulations and organizational policies
- Influence, educate and directly support the platform engineering capabilities of our clients
- Stay current with emerging trends and technologies in cloud computing, data analysis, and software engineering, and proactively identify opportunities to enhance the capabilities of the analytics platform
- Travel is required (30%)

**ABOUT YOU**:

- Proven experience as a cloud engineer and software engineer within either/or product engineering or professional services organizations
- Master’s degree in Computer Science, Engineering, or a related technical field
- 5 years minimum experience
- 3+ years at Senior or Staff level, or equivalent

**Technical Skills and Knowledge**:

- Experience designing and delivering cloud-based distributed solutions GCP, AWS, or Azure certifications are a plus
- Experience building infrastructure as code with tools such as Terraform (preferred), Cloud Formation, Pulumi, AWS CDK, CDKTF, etc.
- Experience building backend APIs, services and/or integrations with Python
- Deep familiarity with nuances of software development lifecycle
- One or more configuration management tools: Ansible, Salt, Puppet, or Chef
- One or more monitoring and analytics platforms: Grafana, Prometheus, Splunk, SumoLogic, NewRelic, DataDog, CloudWatch, Nagios/Icinga
- CI/CD deployment pipelines (e.g. Github Actions, Jenkins, Travis CI, Gitlab CI, Circle CI)
- Practitioner experience with Kubernetes through services like GKE, EKS or AKS is a benefit
- Experience implementation of large-scale structured or unstructured databases, orchestration and container technologies such as Docker, Kubernetes or Terraform
- Experience with workflow orchestration such as dbt, Beam, Airflow, Luigy, Metaflow, Kubeflow, or any other
- Use Git as your main tool for versioning and collaborating
- Exposure to LLMs, Prompt engineering, Langchain a plus
- Strong knowledge in designing API interfaces
- Strong computer science fundaments in data structures, algorithms, automated testing, object-oriented programming, performance complexity, a

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