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Data Analyst / BI Engineer

Scalence L.L.C.

Role overview

Qualifications

  • 3+ years of experience in Data Engineering, Business Intelligence, or Operations Analytics
  • Strong proficiency with SQL and database querying
  • Proven experience building dashboards and reporting views using PLX or equivalent enterprise BI tools
  • Experience writing automation scripts using Python or Client Apps Script

Responsibilities

  • Design, build, and optimize scalable, automated PLX dashboards to track core engineering and testing health metrics
  • Build pipelines and queries to extract, transform, and join data across disparate internal tools
  • Collaborate with team leads and PgMs to define, standardize, and document key operational metrics
  • Replace manually intensive data gathering workflows with automated ETL/data pipelines

About the company

Scalence L.L.C. logo

Scalence L.L.C.

In today’s dynamic and competitive market, success hinges on mastering three key areas: Data Intelligence, Business Resilience, and Digital Experience. At Scalence, a global women-owned IT and BPO solutions provider, we specialize in these critical disciplines through our IT Project and Managed Solutions, propelling your business to new heights. Our commitment to Customer Success and Delivery Excellence drives everything we do. Let us help you unlock new opportunities and propel your business forward. Explore how we can make a difference today!

Company details

Company size501 - 1000

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Job description

Job Title: Data Analyst / BI Engineer (PLX & Cross-System Analytics)
Job Timing- 7:30 PM IST – 4:30 AM IST
Job Type- Remote

Role Overview
We are seeking a Data Analyst / BI Engineer to design, build, and maintain automated dashboards in PLX that aggregate operational performance and quality engineering metrics across disparate internal systems. In this role, you will work closely with Program Managers (PgMs), QA Leads, and Engineering teams to transform scattered manual data—spanning Buganizer, Test Tracker, Client Sheets, and hotlists—into unified, real-time executive dashboards and operational views.
Key Responsibilities
  • Dashboard Architecture & Development: Design, build, and optimize scalable, automated PLX dashboards to track core engineering and testing health metrics.
  • Cross-System Data Integration: Build pipelines and queries to extract, transform, and join data across disparate internal tools (Buganizer, Test Tracker, Client Sheets, internal hotlists, etc.).
  • Metric Standardization: Collaborate with team leads and PgMs to define, standardize, and document key operational metrics, such as:
    • Test Execution Efficiency (Time to Execute / Complete Test Cases)
    • Quality & Defect Leakage (Bugs Leaked to Production, Hotlist tracking)
    • Engineering Efficiency (Bugs Reported vs. Resolved, resolution velocity)
  • Process Automation: Replace manually intensive data gathering workflows with automated ETL/data pipelines (via Python, SQL, Apps Script, or PLX workflows).
  • Data Quality & Governance: Audit underlying data sources for consistency, handle missing/dirty data, and establish data validation practices across team inputs.
Minimum Qualifications
  • Experience: 3+ years of experience in Data Engineering, Business Intelligence, or Operations Analytics.
  • Technical Expertise:
    • Strong proficiency with SQL and database querying.
    • Proven experience building dashboards and reporting views using PLX (or equivalent enterprise BI tools like Looker, Tableau).
    • Experience writing automation scripts using Python or Client Apps Script to interact with REST APIs / JSON payloads.
  • Domain Knowledge: Familiarity with software testing lifecycles, bug-tracking workflows, and QA metrics.
Preferred Qualifications
  • Client Internal Tooling: Direct experience working with Buganizer APIs, Test Tracker, Plx Data Warehouse, and Plx Dashboards.
  • Stakeholder Management: Ability to align cross-functional team leads on consistent metric definitions and reporting frameworks.
  • Data Modeling: Strong understanding of data modeling principles, join logic, and time-delta calculations across un-linked datasets.


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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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