Data Analyst

Posted Yesterday
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Mid level
Cloud • Information Technology • Internet of Things • Professional Services • Software
The Role
Design, build, and maintain Snowflake/dbt data pipelines and models powering customer experience analytics. Write production SQL and Python, implement dbt tests and data quality checks, integrate with GCP and downstream BI (Power BI), and contribute to AI/LLM integration and tooling adoption.
Summary Generated by Built In
Meet the Team

The Customer Listening & Analytics team with Cisco’s Data and Analytics organization, owns the data infrastructure and analytical frameworks that power Cisco’s global customer experience measurement programs. Our data platform underpins NPS measurement, TAC performance analytics, executive business reviews, and customer health scoring—operating across a modern Snowflake/dbt stack with deep integration into GCP and the broader Cisco data ecosystem.

We operate as a lean, high-ownership team where engineers are expected to build, maintain, and continuously improve the foundations that everyone else depends on. Our work is visible at the VP and SVP level, and our architectural decisions have organization-wide impact. We are actively building toward an AI-augmented data platform and have a strong bias toward engineers who want to be part of that trajectory.

Your Impact

As a Data Analytics Engineer on the Customer Listening team, you will own the design, development, and ongoing stewardship of the data infrastructure that powers Cisco’s customer experience analytics. You will work at the intersection of data architecture, pipeline engineering, and AI-augmented analytics—building systems that are clean, testable, and built to scale. This role requires independent ownership, strong technical judgment, and a forward-looking mindset toward AI tooling.

  • Own the end-to-end design and implementation of dbt models within the Customer Listening data platform, including the simplified 6-object architecture, parametric control layer, and plug-and-play organizational hierarchy configurations.
  • Develop and optimize Snowflake-based data pipelines supporting UNIFIED_PARTY_ID resolution, SAV/CAV hierarchy rollups, EBV/EDW reconciliation, and PNPS/TAC metric computation.
  • Write production-grade SQL and Python scripts for data transformation, pipeline automation, and integration with upstream and downstream systems including GCP services and Mosaic.
  • Instrument data pipelines with robust quality frameworks—including dbt tests, row count validation, null assertions, and referential integrity checks—to ensure metric reliability for executive reporting.
  • Collaborate with BI engineers on semantic model handoffs, diagnosing and resolving data-layer issues that manifest in Power BI report outputs.
  • Contribute to AI integration workstreams, including building data tables and pipeline structures that support LLM-generated insight delivery (e.g., Dynamic NPS Forecast AI Summary pipeline).
  • Evaluate and adopt AI-native data tooling—including Snowflake Cortex, dbt Copilot, and related capabilities—in line with the team’s AI future-readiness direction set by VP leadership.
Minimum Qualifications
  • 4+ years of professional experience in data engineering or analytics engineering, with demonstrated ownership of production-grade Snowflake environments including query optimization, RBAC configuration, and schema design.
  • Intermediate to advanced proficiency in dbt, including authoring of incremental models, macros, Jinja templating, snapshot strategy for SCDs, and dbt test frameworks.
  • Expert-level SQL, including window functions, recursive CTEs, complex multi-level aggregations, and query performance profiling in a cloud data warehouse environment.
  • Intermediate Python proficiency for data pipeline scripting, ETL/ELT automation, and lightweight data wrangling using pandas, numpy, or equivalent libraries.
  • Demonstrated experience designing data architecture that supports analytical reporting at enterprise scale—including dimensional modeling, object rationalization, and parametric configuration layer design.
Preferred Qualifications
  • Working familiarity with GCP services (Cloud Storage, Cloud Run, BigQuery, API Gateway) or equivalent Azure data services, with demonstrated ability to integrate cloud-side outputs into a Snowflake-based pipeline.
  • Experience incorporating AI outputs into data pipelines—including consuming LLM API responses as structured data, feature engineering for predictive models, or building tables that support AI summary generation workflows.
  • Exposure to Power BI semantic model consumption and ability to diagnose data-layer issues that surface as report-layer errors, enabling clean handoffs with BI engineering counterparts.
  • Experience with pipeline orchestration tools such as Airflow, Prefect, or dbt Cloud job scheduling, including DAG dependency management and pipeline health monitoring.
  • Git-based development discipline, including branch management, PR workflows, and CI/CD awareness applied to dbt or pipeline codebases; experience with data observability frameworks is a plus.
Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Simply put – we power the future.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Why Cisco? 

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. 

We are Cisco, and our power starts with you. 

Skills Required

  • 4+ years professional experience in data engineering or analytics engineering
  • Production-grade Snowflake experience including query optimization, RBAC configuration, and schema design
  • Intermediate to advanced proficiency in dbt (incremental models, macros, Jinja templating, snapshot strategy, dbt test frameworks)
  • Expert-level SQL including window functions, recursive CTEs, complex aggregations, and query performance profiling
  • Intermediate Python for data pipeline scripting, ETL/ELT automation, and data wrangling (pandas/numpy)
  • Designing enterprise-scale data architecture (dimensional modeling, object rationalization, parametric configuration layers)
  • Working familiarity with GCP services (Cloud Storage, Cloud Run, BigQuery, API Gateway) or equivalent Azure services
  • Experience incorporating AI outputs/LLM APIs into data pipelines and building tables for AI summary generation
  • Exposure to Power BI semantic model consumption and diagnosing report-layer data issues
  • Experience with pipeline orchestration (Airflow, Prefect, or dbt Cloud job scheduling) and DAG dependency management
  • Git-based development discipline, PR workflows, CI/CD applied to dbt or pipeline codebases; data observability experience is a plus
  • Familiarity with Snowflake Cortex and dbt Copilot (AI-native data tooling)

Cisco Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cisco and has not been reviewed or approved by Cisco.

  • Healthcare Strength Comprehensive medical, dental, and vision coverage, mental health support via an EAP, and access to on-site or virtual health centers indicate robust healthcare offerings. Wellness programs, fitness resources, and specialized services further reinforce coverage depth.
  • Leave & Time Off Breadth Generous PTO, a global minimum for paid parental leave, and unique programs like company-wide recharge days and paid volunteer time expand time-away options. Additional offerings such as Critical Time Off and adoption assistance add flexibility for life events.
  • Equity Value & Accessibility Restricted stock units and a discounted employee stock purchase plan are meaningful elements of total compensation. The prominence of equity can materially augment overall pay packages alongside salary and bonuses.

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The Company
HQ: San Jose, CA
77,500 Employees
Year Founded: 1984

What We Do

Cisco (NASDAQ: CSCO) enables people to make powerful connections--whether in business, education, philanthropy, or creativity. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible--providing easy access to information anywhere, at any time. Cisco was founded in 1984 by a small group of computer scientists from Stanford University. Since the company's inception, Cisco engineers have been leaders in the development of Internet Protocol (IP)-based networking technologies. Today, with more than 71,000 employees worldwide, this tradition of innovation continues with industry-leading products and solutions in the company's core development areas of routing and switching, as well as in advanced technologies such as home networking, IP telephony, optical networking, security, storage area networking, and wireless technology. In addition to its products, Cisco provides a broad range of service offerings, including technical support and advanced services. Cisco sells its products and services, both directly through its own sales force as well as through its channel partners, to large enterprises, commercial businesses, service providers, and consumers.

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