Global Data Engineer Senior Specialist

Job Description - Global Data Engineer Senior Specialist

Boston Consulting Group (BCG) | Gurgaon, Haryana, India

Full-Time

Senior Specialist

Job Overview

Category: Details

Company: Boston Consulting Group (BCG)

Job Title: Global Data Engineer Senior Specialist

Location: Gurgaon, Haryana, India

Employment Type: Full-Time

Experience: 4 - 6 Years

Salary: Not Disclosed

Department: Data Engineering / Marketing Technology

Work Mode: Hybrid / Office-based

Office Presence: Approximately 50%

Key Skills: ETL/ELT, SQL, Python, Scala, Data Engineering, Data Pipelines, Data Modelling, Snowflake, Amazon Redshift, Google BigQuery, Data Quality, API Integration, GitHub, CI/CD.

About Boston Consulting Group

Boston Consulting Group (BCG) is a global management consulting firm founded in 1963. BCG partners with business leaders and organizations to solve complex challenges, drive digital transformation, improve business performance, and create sustainable growth.

The company combines business strategy, technology, analytics, and innovation to deliver impactful solutions worldwide.

Job Summary

Boston Consulting Group is seeking an experienced Global Data Engineer Senior Specialist to join its Data Hub Squad in Gurgaon.

The selected candidate will be responsible for designing, developing, testing, and maintaining scalable data pipelines and integrations that support BCG's global Marketing function.

You will work with cloud-based data platforms, external APIs, enterprise databases, and multiple data sources to ensure reliable, secure, and high-quality data availability.

The role requires strong expertise in SQL, Python, ETL/ELT development, cloud data warehouses, and data integration. You will also troubleshoot production issues, optimize data workflows, improve data models, and collaborate with data engineers, analysts, and business stakeholders.

Key Responsibilities

1. Data Engineering & Pipeline Development:

- Design, develop, and maintain scalable data pipelines.

- Build ETL/ELT workflows for processing large datasets.

- Develop data ingestion and transformation processes.

- Integrate data from cloud platforms and on-premises systems.

- Build reliable data workflows for marketing analytics.

- Ensure efficient data processing and availability.

2. Data Integration & API Development:

- Integrate data from multiple external and internal sources.

- Develop API-based data ingestion solutions using Python.

- Connect cloud platforms, enterprise applications, and databases.

- Manage data extraction, transformation, and loading processes.

- Ensure consistent and reliable data integration.

3. Cloud Data Warehousing:

- Work with cloud-based data warehouse platforms.

- Develop and optimize data structures and warehouse models.

- Manage data storage, transformation, and processing workflows.

- Improve query performance and data accessibility.

- Support scalable cloud-based data engineering solutions.

4. Data Quality & Performance Optimization:

- Monitor data pipelines and identify performance issues.

- Investigate data discrepancies and resolve root causes.

- Implement data validation and quality checks.

- Improve code efficiency and pipeline performance.

- Maintain data integrity, accuracy, and consistency.

- Ensure production systems meet agreed service levels.

5. DevOps & Data Engineering Standards:

- Use GitHub and version control systems for code management.

- Support CI/CD pipelines and automated deployments.

- Work with GitHub Actions and Terraform.

- Implement testing and documentation standards.

- Follow data security and engineering best practices.

- Continuously improve development and deployment processes.

6. Collaboration & Stakeholder Management:

- Collaborate with data engineers, analysts, and product owners.

- Work closely with the Chapter Lead and Product Owner.

- Understand business requirements and translate them into technical solutions.

- Coordinate with Marketing teams and technical stakeholders.

- Provide technical documentation and project updates.

Required Qualifications

- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.

- 4 - 6 years of professional experience in Data Engineering.

- Strong hands-on experience with SQL and Python.

- Experience developing ETL/ELT data pipelines.

- Knowledge of data integration and API development.

- Experience with cloud-based data warehouses.

- Understanding of data modelling and database architecture.

- Experience with GitHub and version control systems.

- Working knowledge of CI/CD tools and deployment processes.

- Strong analytical, troubleshooting, and problem-solving skills.

- Excellent communication and collaboration abilities.

Technical Skills

Technical Skill: Requirement

SQL: Mandatory

Python: Mandatory

ETL / ELT: Mandatory

Data Pipeline Development: Mandatory

Data Integration: Mandatory

Data Modelling: Required

Data Quality Management: Required

Snowflake: Preferred

Amazon Redshift: Preferred

Google BigQuery: Preferred

Scala: Preferred

REST API Integration: Required

Git / GitHub: Required

GitHub Actions: Preferred

CI/CD: Required

Terraform: Preferred

Cloud Data Warehousing: Mandatory

Data Testing & Validation: Required

Preferred Candidate Profile

- Strong experience building enterprise-grade data pipelines.

- Hands-on experience with Snowflake, Redshift, or BigQuery.

- Ability to integrate multiple data sources using APIs.

- Experience handling large-scale structured and unstructured datasets.

- Strong understanding of data warehouse architecture.

- Experience troubleshooting production data engineering issues.

- Knowledge of cloud infrastructure and automation.

- Ability to work independently and manage complex engineering tasks.

- Experience supporting marketing analytics or business intelligence platforms is an advantage.

Key Performance Indicators (KPIs)

- Data pipeline reliability and availability.

- Data processing efficiency and performance.

- Data quality and accuracy improvements.

- Successful integration of multiple data sources.

- Reduction in production data issues.

- Query and workflow optimization.

- Timely delivery of engineering projects.

- Compliance with data security and documentation standards.

Work Environment

- Collaborative global Data Hub Squad.

- Regular interaction with data engineers, analysts, and product owners.

- Approximately 50% office or client-site presence, depending on business requirements.

- Opportunities to work with modern cloud data platforms and engineering technologies.

Why Join Boston Consulting Group?

- Work with a globally recognized consulting organization.

- Develop enterprise-scale data engineering solutions.

- Gain exposure to advanced cloud technologies.

- Collaborate with global data and analytics professionals.

- Work on business-critical marketing data initiatives.

- Build expertise in modern data engineering and cloud architecture.

Equal Employment Opportunity

Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration without discrimination based on protected characteristics, in accordance with applicable laws.

ATS / Recruiter Search Keywords:

Senior Data Engineer, Data Engineer, Global Data Engineer, Python Developer, SQL Developer, ETL Developer, ELT Developer, Snowflake Developer, Redshift, BigQuery, Data Pipeline Engineer, Data Integration Engineer, Cloud Data Engineer, Data Warehouse Engineer, Data Modelling, API Integration, GitHub, CI/CD, Terraform, Marketing Data Engineering.

Skills

Data Engineering, SQL, Python, ETL, Data Pipeline, Data Warehousing, Teradata, Big Data, RESTful API, Data Modeling, Snowflake DB