• Full Time
  • Gurgaon

Website Boston Consulting Group

Data Engineer | Boston Consulting Group (BCG X)

Boston Consulting Group (BCG) is hiring a Data Engineer for its BCG X team. BCG X is the firm’s center for tech-driven transformation, combining the world of management consulting with high-end data engineering and AI.

As a Data Engineer here, you won’t just be “managing databases”—you will be building the high-speed data architecture that allows Fortune 500 companies to deploy machine learning and advanced analytics at scale.

🟢 Role Overview & Impact

You will be embedded within “Case Teams,” working directly with consultants and clients to solve high-stakes business problems.

  • Pipeline Architecture: Design, develop, and maintain robust ETL/ELT pipelines to move data from diverse sources into Snowflake, Databricks, or Data Lakes.

  • Big Data Mastery: Leverage PySpark and distributed computing to process massive datasets that traditional systems can’t handle.

  • Cloud Native Solutions: Build scalable, secure, and cost-effective environments on AWS, GCP, or Azure.

  • DevOps & Automation: Own the “Productization” of data. This includes building CI/CD pipelines(Jenkins/GitHub Actions) and orchestrating workflows using Airflow.

  • Analytical Bridge: Translate technical data structures into business insights, often packaging your results into high-level synthesis for senior consultants and stakeholders.

📊 Candidate Profile & Benchmarks (2026)

Based on 2026 market standards for Tier-1 consulting firms (MBB) in the Data Engineering domain:

Metric Details
Experience Level 2–4 Years in Data Engineering.
Estimated CTC ₹22 LPA – ₹32 LPA (Reflecting the high-entry bar for BCG X).
Education Bachelor’s or Master’s in Computer Science or Engineering.
Key Tech Stack Python, PySpark, Snowflake, SQL, Airflow.
Preferred Background Previous experience in consulting or high-tech commercial settings.

🎯 Required Technical Skills

  • The Big Data Core: Deep knowledge of PySpark, Hive, and Databricks. You must understand Spark cluster management and optimisation.

  • Data Warehousing: Advanced proficiency in Snowflake or similar cloud warehouses.

  • Automation & Infra: Hands-on experience with Terraform/CloudFormation (IaC) and containerization via Docker/Kubernetes.

  • ML Awareness: A basic understanding of Machine Learning system design (how to feed data into a model pipeline).

  • NoSQL Exposure (Bonus): Familiarity with MongoDB, Cassandra, or HBase.

Upload your CV/resume or any other relevant file. Max. file size: 2 GB.