Expert Manager, Data Engineering

Employment type

Permanent Full-Time

Location(s)

Paris

Paris

Description & Requirements

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.


WHAT YOU’LL DO


As an Expert Manager, Data Engineering you will lead the development and application of technical solutions to address complex  problems in various industries. You will guide a diverse engineering team through the entire engineering life cycle. Your responsibilities will include designing, developing, optimizing, and deploying cutting-edge data engineering solutions and infrastructure at the production scale required by the world’s largest companies.


  • Lead development of data and software solutions to address large-scale enterprise challenges for Bain's clients, serving as the data engineer and expert within a cross-functional team
  • Lead development of long-lasting products that support internal or client needs
  • Collaborate closely with and influence general consulting teams to identify analytics solutions for client business problems and to execute those solutions
  • Collaborate with data engineering leaders to develop and advocate for modern data engineering concepts to both technical audiences and business stakeholders
  • Enable data and technology for data science, analytics, and other application use cases via data engineering
  • Transformations at scale including cleaning, enriching, de-duping, joining and correlated on structured, semi-structured or unstructured data
  • Defining and implementing new and innovative deployment techniques, tooling, and infrastructure automation within Bain the full software development life cycle including designing, writing documentation and unit/integration tests, and conducting code reviews for data engineering solutions
  • Participate in infrastructure engineering for data ecosystem including development, testing, deployment and release
  • Work with the team and other senior leaders to create a great working environment that attracts other great engineers
  • Coach engineering teams at our clients and partners to raise their capabilities and ensure that our work is successfully deployed to the highest standards
  • Drive best demonstrated practices in data engineering, and share learnings with team members in AAG about theoretical and technical developments in data engineering
  • Drive industry-leading innovations that translate into great impact for our clients in case work 
  • Act as PD Advisor as needed
  • Participate in recruiting and onboarding for other team member
  • Travel is required (30%)


ABOUT YOU


  • Master’s degree in Computer Science, Engineering, or a related technical field
  • 7 years minimum experience
  • 4 years minimum at Lead or Staff level, or equivalent
  • Proven experience in  end to end data and software engineering within either/or product engineering or professional services organizations; including project setup, test cases, dependency, and build management
  • Commercial acumen and understanding of business models


Technical Skills and Knowledge:

  • Expert knowledge (5+ years) of Python, Scala, C/C++, Java, C#, Go, or similar programming language
  • Experience in deploying serverless data pipelines through containerization and terraform orchestration
  • Experience in data ingestion using one or more modern ETL compute and orchestration frameworks (Airflow, Beam, Luigy, Spark, Nifi or any other)
  • Experience (5+ years) of  SQL or NoSQL databases: PostgreSQL, SQL Server, Oracle, MySQL, Redis, MongoDB, Elasticsearch, Hive, HBase, Teradata, Cassandra, Amazon Redshift, Snowflake
  • Experience with Cloud platforms and services (AWS, Azure, GCP, etc.) or Kubernetes via Terraform automation, and associated deep understanding of failover, high-availability, and high scalability
  • Experience with DevOps, CI/CD, Github Actions, version control and Git workflows
  • Experience scaling and optimizing schema and performance turning SQL and ETL pipelines in data lake and data warehouse environments
  • Experience (1+ years) overseeing data engineer team members
  • Strong computer science fundaments in data structures, algorithms, automated testing, object-oriented programming, performance complexity, and implications of computer architecture on software performance
  • Experience working according to agile principles 


Interpersonal Skills:

  • Strong interpersonal and communication skills, including the ability to explain and discuss technicalities of solutions, algorithms and techniques with colleagues and clients from other disciplines
  • Curiosity, proactivity and critical thinking
  • Ability to collaborate with people at all levels and with multi-office/region teams
  • Ability to work independently and juggle priorities to thrive in a fast paced and ambiguous environment, while also collaborating as part of a team in complex situations