Bachelors or Masters degree in Computer Science, Engineering, Technology, Data Science or a related technical field.

- 6+ 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 involvement in 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 and modern data platforms, including Spark-based processing, performance tuning, and large-scale data system design.

- Deep experience with technologies such as Spark, DBT, Databricks, Snowflake, Hive, Hadoop or equivalent big data and analytics ecosystems.

- Robust cloud engineering experience across AWS, Azure, or GCP, with expertise in at least one cloud ecosystem.

- On-ground exposure to GenAI implementation patterns, including RAG, retrieval pipelines, LLM application architecture, workflow design, evaluation, monitoring and deployment.

- Responsible use of AI tools across the SDLC to improve engineering productivity while maintaining quality, security and delivery accountability.





- Hands-on experience building trusted data foundations, including data modeling, pipeline productization, orchestration, CI/CD, containerization and observability.

- Practical experience with data governance, metadata, cataloging, lineage, privacy and security in enterprise data environments.

- Strong client-facing communication skills, with the ability to influence senior stakeholders and handle ambiguity, trade-offs, and difficult delivery conversations.

Good to have

- Prior consulting experience or experience working directly with senior stakeholders driving solution delivery.

- Experience in Retail, Telecom or other data-rich industries with complex enterprise data landscapes.

- Experience with NoSQL, streaming, messaging and event-driven architectures.

- Exposure to ML engineering or advanced analytics integration in production environments.

- Experience making pragmatic build-versus-buy recommendations across enterprise data and GenAI platforms.

- Good understanding of enterprise architecture transformations like Lakehouse and Data Mesh, along with its advantages and drawbacks

📌 Lead AI Data Engineer (Gurugram)
🏢 Mount Talent Consulting
📍 Gurugram