BCG X Hiring Drive 2024 For Data Engineer – X Delivery | Location Bengaluru

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BCG X Hiring Drive 2024: BCG X Hiring Drive 2024 for its Data Engineer – X Delivery. BCG X Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Bachelor’s / Master’s degree in computer science engineering/technology. if you are interested, please apply as soon as possible.

Company Name: BCG X

Role: Data Engineer – X Delivery

Location: Bengaluru

Experience: 2-4 years

Qualification: Bachelor’s / Master’s degree in computer science engineering/technology

Batch: Any

Job Type: Full Time

Salary: 17.5 LPA (Expected)

BCG X Hiring Drive 2024

Job Description:

  • As a part of BCG’s X team, you will work closely with consulting teams on a diverse range of advanced analytics and engineering topics.
  • You will have the opportunity to leverage analytical methodologies to deliver value to BCG’s Consulting (case) teams and Practice Areas (domain) through providing analytical and engineering subject matter expertise.
  • As a Data Engineer, you will play a crucial role in designing, developing, and maintaining data pipelines, systems, and solutions that empower our clients to make informed business decisions.
  • You will collaborate closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver high-quality data solutions that meet our clients’ needs.


  • Bachelor’s / Master’s degree in computer science engineering/technology
  • At least 2-4 years within relevant domain of Data Engineering across industries and work experience providing analytics solutions in a commercial setting.
  • Consulting experience will be considered a plus.
  • Proficient understanding of distributed computing principles including management of Spark clusters, with all included services – various implementations of Spark preferred.
  • Basic hands-on experience with Data engineering tasks like productizing data pipelines, building CI/CD pipeline, code orchestration using tools like Airflow, DevOps etc.
  • Strong communication skills, enabling effective collaboration with both technical and non-technical team members.
  • You should be strong in analytical solutioning with hands on experience in advanced analytics delivery, through the entire life cycle of analytics.
  • Strong analytics skills with the ability to develop and codify knowledge and provide analytical advice where required.
  • Software engineering concepts and best practices, like API design and development, testing frameworks, packaging etc.
  • Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
  • Knowledge on web development technologies.
  • Understanding of different stages of machine learning system design and development.


  • Delivering original analysis and insights to case teams, typically owning all or part of an analytics module whilst integrating with a case team.
  • Design, develop, and maintain efficient and robust data pipelines for extracting, transforming, and loading data from various sources to data warehouses, data lakes, and other storage solutions.
  • Building data-intensive solutions that are highly available, scalable, reliable, secure, and cost-effective using programming languages like Python and PySpark.
  • Deep knowledge of Big Data querying and analysis tools, such as PySpark, Hive, Snowflake and Databricks.
  • Broad expertise in at least one Cloud platform like AWS/GCP/Azure.
  • Working knowledge of automation and deployment tools such as Airflow, Jenkins, GitHub Actions, etc., as well as infrastructure-as-code technologies like Terraform and CloudFormation.
  • Good understanding of DevOps, CI/CD pipelines, orchestration, and containerization tools like Docker and Kubernetes.
  • Basic understanding on Machine Learning methodologies and pipelines.
  • Communicating analytical insights through sophisticated synthesis and packaging of results (including PPT slides and charts) with consultants, collecting, synthesizing, analyzing case team learning & inputs into new best practices and methodologies.

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