Join Boston Consulting Group's X Delivery team as a Senior Delivery AI Data Engineer. You will be instrumental in leveraging cutting-edge AI and data engineering methodologies to support BCG's consulting teams and practice areas. This role offers the chance to provide subject matter expertise and accelerated execution for advanced analytics topics.

Your contributions will involve collaborating with teams to define, develop, and implement impactful data and AI solutions. You'll enhance case leadership capabilities by offering deep technical insights into relevant technologies and processes, ensuring the creation of high-quality, efficient solutions for complex client challenges.

As a Senior Delivery AI Data Engineer, you will own the complete lifecycle of data engineering modules, pipelines, and data products across cloud, hybrid, and on-premise environments. This includes end-to-end delivery for ingestion, transformation, data modeling, orchestration, and productionization of analytics and AI use cases.

You will build robust batch, streaming, and API-driven data solutions, emphasizing maintainability, documentation, and client-readiness. A key aspect of this role involves creating trusted, reusable data assets with strong adherence to data quality, governance, cataloging, lineage, observability, and access control principles. Additionally, you will implement GenAI and Agentic AI workflows, ensuring responsible use of AI tools to boost engineering productivity while upholding code quality and delivery accountability.

We are seeking a candidate with a Bachelor’s or Master’s degree in Computer Science, Engineering, Technology, Data Science, or a related technical field, complemented by 4-6 years of relevant experience. Essential technical proficiencies include advanced SQL, complex querying, performance optimization, and data modeling for large analytical datasets. A strong command of at least one major programming language like Python, Java, or Scala is also critical.

Solid understanding of distributed computing, Spark-based processing, orchestration, and scalable data system design is required. Practical experience with GenAI & Agentic AI implementation patterns, cloud data services (AWS, Azure, or GCP), and productizing data pipelines with DevOps practices is essential. Familiarity with technologies such as Spark, dbt, Databricks, Snowflake, or equivalent data ecosystems is highly valued.