29 days ago
Bengaluru, IndiaSenior
Responsibilities
- Lead exploratory data analysis across structured and unstructured datasets to identify trends and inform architecture.
- Translate complex business requirements and diverse source-system data into scalable, resilient data solutions integrated with the Enterprise Data Warehouse.
- Architect, develop, optimize, and oversee ETL/ELT pipelines for ingestion, transformation, and publication into Snowflake.
- Define standards and oversee analytics-ready data models using dbt, including modular design, reuse, testing, and CI/CD integration.
- Design and implement a reusable semantic layer for AI, agentic solutions, dashboards, and other high-volume consumers.
- Integrate Snowflake Cortex and other AI/LLM capabilities into data pipelines for advanced analytics and automation.
- Design advanced data consumption layers including dashboards, reports, conversational analytics, and agentic solutions.
- Apply databases, relational databases, cloud services, and scripting languages to data engineering work.
- Drive data cleansing, scrubbing, integration, quality frameworks, observability, lineage, governance, and access control.
- Serve as a technical liaison with architects, analysts, business stakeholders, onsite teams, and engineering groups to define data strategies and roadmaps.
- Establish technical governance, version control, CI/CD, security, scalability, and modern data stack best practices.
- Use cloud-native data processing and orchestration services and apply Agile, Scrum, or Kanban practices.
- Provide technical guidance and mentorship to junior data engineers.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- At least 8 years of progressive data engineering experience architecting and leading cloud data warehousing and modern data platform implementations.
- At least 4 years of experience leading or architecting AI and agentic solutions on platforms such as Snowflake, AWS, or GCP.
- Expert-level proficiency with the Snowflake Data Cloud, including advanced features, security, and operational practices.
- Expert-level proficiency with dbt for complex data models, automated testing, and CI/CD integration.
- Mastery of SQL and Python for scalable data processing, automation, and API integration.
- At least 7 years of experience with leading BI and reporting tools such as Sigma or Power BI, including data visualization best practices.
- Expertise implementing and managing enterprise data quality, observability, and lineage frameworks and tools.
- Practical understanding of advanced Snowflake capabilities including zero-copy cloning, secure data sharing, external tables, Snowpark, dynamic tables, and MCP gateways.
- Experience with enterprise data and solution architectures, including data mesh or data fabric principles.
- Understanding of analytics ecosystems, BI and reporting tools such as Tableau and ThoughtSpot, and downstream consumption patterns.
- Experience guiding technical teams and presenting complex technical concepts to senior leadership.
- Snowflake Gen AI certification is preferred.
Tech Stack
Categories
Data Engineering
About Cisco
Cisco designs and sells networking, security, and collaboration platforms for enterprises, service providers, and governments, spanning routers and switches, Wi‑Fi, firewalls, zero‑trust, observability, and cloud-managed IT (Meraki) plus Webex. Its business model mixes hardware, software subscriptions, and support/consulting services. Founded in 1984 and headquartered in San Jose, California, Cisco is a public company traded on Nasdaq and serves customers across data centers, campuses, and service provider networks.