Data Analyst

123 Cisco Systems (India) Private Limited; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

123 Cisco Systems (India) Private Limited is seeking a Data Analytics Engineer to design, develop, and manage the data infrastructure that drives customer experience analytics. The ideal candidate will have over 4 years of experience in data engineering, with expertise in Snowflake environments and a strong command of SQL and Python.

This role involves collaborating with BI engineers, optimizing data pipelines, and integrating AI tools into data workflows. Strong analytical skills and a proactive mindset are essential. Candidates should be capable of independently owning projects from design to execution.

Qualifications

• 4+ years professional experience in data engineering or analytics.
• Advanced proficiency in dbt for managing incremental models and testing.
• Expert-level SQL skills in a cloud data warehouse environment.

Responsibilities

• Design and implement data infrastructure supporting customer experience analytics.
• Develop Snowflake-based data pipelines with robust quality frameworks.
• Collaborate with BI engineers on diagnosing data-layer issues.

Skills

SQL

Python

dbt

Data Engineering

Data Architecture

Tools

Snowflake

GCP

Power BI

Airflow

Job description

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. You will 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. You will develop and optimize Snowflake‑based data pipelines supporting UNIFIED_PARTY_ID resolution, SAV/CAV hierarchy rollups, EBV/EDW reconciliation, and PNPS/TAC metric computation. You will write production‑grade SQL and Python scripts for data transformation, pipeline automation, and integration with upstream and downstream systems including GCP services and Mosaic. You will 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. You will collaborate with BI engineers on semantic model handoffs, diagnosing and resolving data‑layer issues that manifest in Power BI report outputs. You will 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). You will 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.