Job Description

Job Title: Assistant Manager

**Job Family -**Data Analytics

Role Overview: The role is responsible for designing, building, and maintaining backend data pipelines and analytical datasets that support large‑scale business operations. The position focuses on advanced SQL development, ETL processes, and data modelling, along with analytical insights and dashboard creation using Google’s data ecosystem.

The role works closely with stakeholders, handling structured data at scale and enabling data‑driven decision‑making through reliable, well‑governed datasets and dashboards.

It is a core backend data engineering and analytics role.

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Key Roles & Responsibilities

Data Engineering & ETL

• Design, develop, and maintain robust SQL‑based data pipelines supporting ETL workflows.

• Work extensively on advanced SQL (Google SQL / Big Query‑style SQL) for data extraction, transformation, and aggregation.

• Develop and optimize PLX scripts for backend data processing and automation.

• Ensure data quality, integrity, and performance across large datasets.

• Troubleshoot and resolve data pipeline failures, performance issues, and data inconsistencies.

Data Analysis & Analytics Enablement

• Analyze complex datasets to identify trends, patterns, and insights relevant to business and operational needs.

• Translate analytical requirements into optimized datasets and data models.

• Partner with cross‑functional teams to understand data requirements and deliver scalable solutions.

Dashboarding & Visualization

• Build and maintain PLX dashboards and analytical views for stakeholders.

• Develop dashboards using Looker Studio (preferred) for insights and performance monitoring.

• Ensure dashboards are accurate, scalable, and aligned to defined metrics and business logic.

Governance & Best Practices

• Follow data engineering best practices including version control, documentation, and reusable SQL patterns.

• Ensure compliance with data access controls, security standards, and internal governance policies.

• Participate in reviews, audits, and continuous improvement initiatives for data pipelines.

Education

• Any Graduate (Engineering / Computer Science / Mathematics / Statistics preferred)

Experience

Must Have

• 4–8 years of hands‑on experience in backend data engineering or analytics roles

• Strong experience working with advanced SQL in large‑scale data environments

• Proven experience with ETL processes and data pipeline development

• Experience working in structured, process‑driven environments supporting enterprise clients

Technical Skills

Must Have

• Advanced SQL (complex joins, CTEs, window functions, performance tuning)

• Strong understanding of ETL concepts, data modeling, and data transformations

• Hands‑on experience with PLX scripts and PLX dashboards

• Strong analytical and problem‑solving skills

Good to Have

• Experience with Google Workspace tools (Docs, Sheets, Slides)

• Google Apps Script for automation

• Looker Studio for dashboarding and analytics

• Programming/scripting experience in Python, JavaScript, or VBA