Data Analyst Commercial Analytics / Data & AI

philodesign technologies inc

Data Analyst Commercial Analytics / Data & AI

philodesign technologies inc

5-7 Years

Not Disclosed

India

Posted 18 hours ago
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Job Description

Data Analyst – Commercial Analytics / Data & AI

Experience: 5+ Years

Openings: 2

Work Mode: 100% Remote

Location: India / Remote

Shift: IST

Engagement: Contract / Project-Based

Joining: Immediate / Short Notice Preferred

Role Overview

We are looking for an experienced Data Analyst – Commercial Analytics / Data & AI to join a high-impact Data & AI team.

The ideal candidate will combine strong advanced SQL, Databricks and/or Amazon Redshift, commercial analytics, and business-to-technical translation skills.

You will work closely with Sales, Marketing, Commercial Excellence, Data Engineering, BI, and AI/ML teams to translate complex business requirements into analytical datasets, SQL logic, data-quality validations, dashboards, and actionable business insights.

The role requires someone who can independently understand a business process, identify the relevant source data, develop complex SQL, validate analytical results, and communicate findings to both technical and non-technical stakeholders.

Key Responsibilities

1. Business Process Translation & SQL Development

Translate commercial processes into analytical requirements and SQL solutions.
Work with processes including:
Sales & Distribution
Go-to-Market (GTM)
Pricing & Promotions
Sales Returns
Rebates & Incentives
Marketing Campaigns
Distributor & Retailer Networks
Develop, optimize, and maintain complex SQL queries, views, and analytical datasets.
Work extensively with Databricks and/or Amazon Redshift.
Build business-ready datasets across Silver and Gold data layers.
Develop SQL logic using:
CTEs
Complex joins
Window functions
Subqueries
Aggregations
Query optimization
Translate business rules into documented technical specifications and SQL logic.

2. Commercial & Sales Analytics

Analyze commercial and sales performance across regional markets.
Work with sell-in and sell-out data.
Analyze:
Sales performance
Pricing effectiveness
Promotions
Rebates
Loyalty programs
Marketing campaigns
Sales targets
Forecasting
Inventory and demand trends
Identify sales gaps, market trends, bottlenecks, and business opportunities.
Develop analytical datasets supporting BI and AI/ML use cases.
Provide actionable insights to Sales, Marketing, and Commercial Excellence stakeholders.

3. Data Quality & Reconciliation

Develop SQL-based data-quality and validation checks.
Reconcile analytical results against source systems.
Investigate data discrepancies, anomalies, and inconsistencies.
Collaborate with Data Engineering teams to improve data pipelines, tables, views, and data models.
Document:
Business rules
Data mappings
Transformations
Data-quality rules
Analytical logic

4. Data Warehousing & Data Modelling

Work with large-scale commercial datasets.
Apply strong knowledge of data warehousing and dimensional modelling.
Understand and work with:
Star schema
Snowflake schema
Fact and dimension tables
Hierarchies
Data transformations
Silver/Gold data layers
Build analytical datasets suitable for BI and AI/ML consumption.

5. Dashboarding & BI

Develop and maintain analytical datasets supporting commercial dashboards.
Work with Qlik Sense/QlikSense for sales and commercial analytics.
Where applicable, integrate Qlik Sense with Databricks or Redshift.
Experience with Power BI or Tableau is an advantage.

6. Stakeholder Collaboration

Work directly with business stakeholders to understand requirements.
Convert business requirements into technical specifications and SQL solutions.
Communicate analytical findings clearly to technical and non-technical audiences.
Collaborate with:
Sales
Marketing
Commercial Excellence
Data Engineering
BI
AI/ML
Business stakeholders

Mandatory Skills

Candidates must have strong hands-on experience in:

5+ years of Data Analytics / Data Analyst experience
Advanced SQL
Complex SQL queries including CTEs, joins, window functions, subqueries, and aggregations
Databricks and/or Amazon Redshift
Data warehousing and dimensional modelling
Data validation and reconciliation
Business requirement → technical requirement → SQL translation
Commercial, Sales, or Marketing Analytics
Large-scale datasets and cloud data platforms
Strong stakeholder communication

Commercial Domain Experience

Strong experience in commercial or sales analytics is required, with exposure to areas such as:

Order-to-Cash (O2C)
Sales & Distribution
Distributor/Retailer Analytics
Pricing
Sales Incentives & Rebates
Promotions
Loyalty Programs
Marketing Campaign Analytics
Sales Targets
Forecasting
Sell-in / Sell-out Analytics

Industry Experience – Important

Minimum 2 years of relevant industry experience is strongly preferred and may be required based on project needs.

Preferred industries include:

Agriculture / AgTech
Crop Protection
Seeds
Agrochemical
Manufacturing
FMCG
Consumer Products
Distributor-driven businesses

Candidates with experience working with structured distributor, retailer, dealer, or channel networks will be highly preferred.

Source System Experience

Working knowledge of commercial data from the following systems is highly preferred:

SAP SD

Sales Orders
Deliveries
Billing
Returns
Rebates

Salesforce / SFDC

Sales Targets
Business Growth Plans
Customer/Account Data
Special Pricing

Additional exposure to digital customer/grower engagement or field-force platforms is an advantage.

Good-to-Have Skills

Qlik Sense / QlikSense
Power BI
Tableau
Python
PySpark
Cloud data platforms
AI/ML analytical datasets
Data & AI environments
Experience supporting AI/ML teams with analytical datasets

Key Competencies

Strong analytical and problem-solving ability
Advanced SQL capability
Excellent attention to detail
Strong data-quality mindset
Business-to-Technical translation
Commercial mindset
Strong stakeholder management
Ability to investigate and reconcile data discrepancies
Strong documentation and communication skills
Ability to work independently
Ability to manage multiple analytical requirements in a remote environment

Ideal Candidate

The ideal candidate should be able to independently follow this complete analytical process:

Understand Business Process → Identify Source Data → Develop Complex SQL → Build Analytical Dataset → Validate & Reconcile Results → Identify Insights → Deliver Dashboard/BI-Ready Data

We are looking for a hands-on Data Analyst with strong technical SQL and cloud data-platform experience, not someone focused primarily on reporting or dashboard creation.

Not a Fit For

Candidates whose experience is primarily limited to: