5 months ago
Gurgaon, IndiaStaff+
Responsibilities
- Own the design, build, and operation of production-grade data platforms and pipelines across cloud, hybrid, and on-premise environments.
- Lead end-to-end data engineering delivery across ingestion, transformation, data modeling, orchestration, serving, and productionization.
- Architect scalable batch, streaming, real-time, and API-driven data solutions for business-critical analytics and AI use cases.
- Design trusted and reusable data foundations with data quality, governance, cataloging, lineage, and access control practices.
- Lead GenAI implementations involving RAG, retrieval design, LLM application patterns, workflow design, evaluation, and production deployment.
- Write, review, and improve engineering work in Python, Java, or Scala across distributed data systems and modern data platforms.
- Build reusable data engineering assets and implementation patterns for client engagements.
- Translate ambiguous business problems into scalable data and AI engineering solutions with clients, consulting teams, and technical stakeholders.
- Lead and mentor engineers while addressing architecture, code quality, documentation, DevOps, governance, and production readiness.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Technology, Data Science, or a related technical field.
- 8+ years of relevant experience in data engineering, data platforms, or enterprise AI/data solution delivery.
- Proven experience leading production-grade data engineering programs with hands-on architecture, implementation, code review, deployment, and operationalization.
- Expert proficiency in at least one major programming language such as Python, Java, or Scala.
- Strong understanding of distributed computing, Spark-based processing, performance tuning, and large-scale data system design.
- Deep experience with Spark, DBT, Databricks, Snowflake, Hive, Hadoop, or equivalent big data and analytics ecosystems.
- Strong cloud engineering experience across AWS, Azure, or GCP, with expertise in at least one cloud ecosystem.
- Hands-on experience with GenAI implementation patterns including RAG, retrieval pipelines, LLM application architecture, workflow design, evaluation, monitoring, and deployment.
- Experience building trusted data foundations through data modeling, pipeline productization, orchestration, containerization, and observability.
- Practical experience with data governance, metadata, cataloging, lineage, privacy, and security in enterprise data environments.
- Strong client-facing communication skills and the ability to influence senior stakeholders, manage ambiguity, and handle delivery trade-offs.
- Prior consulting or senior stakeholder solution-delivery experience is preferred.
- Experience in Retail, Telecom, or other data-rich industries is preferred.
- Experience with NoSQL, streaming, messaging, event-driven architectures, ML engineering, advanced analytics integration, enterprise platform build-versus-buy decisions, Lakehouse, or Data Mesh is preferred.
Tech Stack
Apache HadoopApache HiveApache SparkAWSAzureDatabricksdbtGoogle Cloud PlatformJavaPythonScalaSnowflake
Categories
AI ApplicationsData Engineering
About BCG
Boston Consulting Group provides management consulting, technology, and design services to large enterprises, governments, and nonprofits, helping with strategy, digital transformation, and operations. The firm works on a project-based, fee-for-service model and also incubates products and ventures through BCG X. Founded in 1963 and headquartered in Boston, it is a global partnership with offices worldwide.