Lead, Data Engineer

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 a Glassdoor Best Place to Work and we have maintained a spot in the top four since its founding in 2009. We believe that diversity, inclusion and collaboration are 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.

WHO YOU’LL WORK WITH

Working alongside our generalist consultants, Bain's Advanced Analytics Group (AAG) helps clients across industries solve their biggest problems using our expertise in data science, engineering, customer insights, statistics, machine learning, data management, and supply chain analytics. Stationed in our global offices, AAG team members hold advanced degrees in computer science, engineering, AI, data science, physics, statistics, mathematics, and other quantitative disciplines, with backgrounds in a variety of fields including tech, data science, marketing analytics and academia.

CORE RESPONSIBILITIES

• Partner with Data Science, Machine Learning, and Platform Engineering teams to develop and deploy production quality code
• Develop and champion modern Data Engineering concepts to technical audience and business stakeholders
• Implement new and innovative deployment techniques, tooling, and infrastructure automation within Bain and our clients
• Master’s degree in Computer Science, Engineering, or a related technical field. 
• 3+ years at Senior or Staff level, or equivalent
• 3+ years of experience programming with Python, Scala, C/C++, Java, C#, Go, or similar programming language.
• 3+ years of experience with SQL or NoSQL databases: PostgreSQL, SQL Server, Oracle, MySQL, Redis, MongoDB, Elasticsearch, Hive, HBase, Teradata, Cassandra, Amazon Redshift, Snowflake.
• Experience in deploying serverless data pipelines through containerization and terraform orchestration 
• Industry level experience of working with public cloud environments (AWS, GCP, or Azure), and associated deep understanding of failover, high-availability, and high scalability  
• Scaling and optimizing schema and performance tuning SQL and ETL pipelines in data lake and data warehouse environments.
• Strong computer science fundaments in data structures, algorithms, automated testing, object-oriented programming, performance complexity, and implications of computer architecture on software performance.
• Data ingestion using one or more modern ETL compute and orchestration frameworks (e.g. Apache Airflow, Luigi, Spark, Apache Nifi, and Apache Beam).
• Version control and git workflows
• Strong interpersonal and communication skills, including the ability to explain and discuss complexmathematical and machine learning technicalities with colleagues and clients from other disciplines at their level of cognition 
• Curiosity, proactivity and critical thinking 
• Travel is required (~30%)