You will lead a QE team building a cross-platform BI Test Automation Framework in

Python and Playwright that validates enterprise dashboards on

Tableau, Power BI, and Looker

. The core of the role is engineering test cases that are written once and run against all three platforms through a shared, tool-agnostic Python layer, covering data accuracy against

BigQuery and source systems, filters and interactions, row-level security, visual rendering, and dashboard performance.

Key Responsibilities

- Strategy &
- Leadership:

Own the BI QE strategy across functional, data, security, visual regression, and performance testing for Tableau, Power BI, and Looker; lead a team of QE engineers, set coding standards, review pull requests, and provide sprint-level quality sign-off.

- Reusable Framework Architecture:

Design and own a platform-agnostic Python framework in which a single test case runs against Tableau, Power BI, and Looker. Use an adapter / Page Object pattern with a common BI interface (open dashboard, apply filter, set parameter, drill down, read KPI / table values, export data), with one adapter implementation per platform, so that new dashboards and platforms plug in without rewriting tests.

- Playwright Automation:

Build robust UI automation with

Playwright for Python

, handling embedded iframes, shadow DOM, canvas / SVG-rendered visuals, lazy-loaded tiles, and asynchronous query rendering, using reliable locator strategies, explicit wait conditions, and network interception rather than fixed sleeps.

- Test Authoring &

- Data-Driven Design:

Author test cases with pytest

(fixtures, parametrisation, markers, plugins), optionally with pytest-bdd / Gherkin for business-readable scenarios; externalise dashboards, filters, expected KPIs, and user roles into YAML / JSON / CSV test data so the same suite scales across reports, environments, and platforms.

- BI Data Validation:

Reconcile values shown on dashboards (KPIs, crosstabs, aggregations, totals, filtered views) against the expected results from

BigQuery SQL or source systems; use platform exports and APIs (





Tableau REST / Metadata API

,

Power BI REST API

,

Looker API SDK

) to extract underlying data where UI scraping is unreliable.

- Security &

- Visual Validation:

Automate row-level and column-level security checks by executing the same scenarios under multiple user personas; implement visual regression testing with baseline screenshot comparison and tolerance thresholds for layout, branding, and rendering defects.

- Performance Testing:

Measure dashboard load, filter-response, and render times using Playwright tracing, browser Performance APIs, and network timings; run concurrent-user scenarios with Python tooling and validate results against defined SLAs.

- CI/CD &

- Release Gating:

Run suites in parallel through

GitHub Actions with smoke, regression, and full-suite release gates; publish rich reports with screenshots, traces, and videos attached for failed tests.

Required Technical Skills

- Python (Core Requirement):

Expert-level

Python 3

with strong object-oriented design: abstract base classes, protocols, design patterns (Adapter, Factory, Page Object, Strategy), type hints, packaging, and dependency management (

Poetry / uv / pip

). Proven ability to build reusable libraries, not just scripts, with clean code, linting (

ruff / black / mypy

), and unit tests for the framework itself.

- Playwright for Python:

Deep hands-on experience with

Playwright (Python, sync and async APIs)

: locators, auto-waiting, frame and shadow DOM handling, network interception and mocking, authentication state reuse, tracing, screenshots, video capture, and cross-browser execution (Chromium, Firefox, WebKit).

- Test Frameworks:

Solid proficiency in pytest

(fixtures,



conftest hierarchies, parametrisation, custom plugins and hooks, markers); working knowledge of pytest-bdd or behave for BDD-style scenarios.

- BI Platforms:

Practical testing experience on at least two of

Tableau

(Server / Cloud),

Power BI

(Service / Embedded), and

Looker

(Explores, Looks, dashboards, LookML), with an understanding of each platform's DOM structure, rendering model, filters, parameters, and security model.

- BI APIs &
- Data Validation:

Experience with tableauserverclient / Tableau REST and Metadata APIs

,

Power BI REST API

, and the

Looker Python SDK

; strong

SQL

(preferably

BigQuery

) for writing expected-result queries; use of pandas for dataset comparison and tolerance-based numeric checks.

- CI/CD Execution:

Experience orchestrating parallel test pipelines in

GitHub Actions

(or Jenkins / Azure DevOps), including Docker-based execution, secrets management, and scheduled regression runs.

- Reporting:

Experience producing actionable test reports with

Allure or equivalent, including screenshots, Playwright traces, and videos for failed tests, plus platform-wise coverage and trend metrics.

Qualifications

- 5+ years of experience in Quality Engineering, with at least 3 years leading test automation for BI / analytics or data platform programmes.

- Demonstrated delivery of a

Python-based Playwright automation framework in production use, ideally one reused across multiple applications or BI tools.

- Proven ability to design for reuse: a track record of building shared test libraries, abstraction layers, and data-driven suites that reduce per-dashboard automation effort.

- Experience leading and mentoring a QE team, conducting code reviews, and setting automation engineering standards.

- Strong analytical mindset to perform root cause analysis on dashboard discrepancies across the semantic layer, data model, and source data.

Good to have: experience with Selenium-to-Playwright migration, accessibility testing (axe-core), GCP / BigQuery

📌 Lead Quality Engineer (BI Automation – Playwright & Python) (Chennai)
🏢 Cittabase Solutions
📍 Chennai