Value Data Engineer

Logile, Inc.; Khordha; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Logile, Inc. in Bhubaneswar, India seeks a Value Data Engineer to steward value data and analytics across pre-sales, project delivery and post-go-live reviews, collaborating with Account Managers and Customer Success to ground value in real customer data.

You will build and maintain ETL/ELT pipelines, interrogate live and platform usage data, and develop ROI evidence to support renewals and expansion conversations.

Qualifications

• Bachelor's degree in computer science, engineering, data analytics, or commensurate work experience.
• 5-8 years of experience as a Data Engineer, Analytics Engineer, or similar role, ideally with exposure to commercial/value-analytics.
• Strong SQL and Python/R; experience building and maintaining ETL/ELT pipelines against large datasets.
• Writing scripts for statistical analysis, handling API requests, or executing predictive models.
• Experience with BI/analytics and dashboarding tools (Power BI, Tableau, Looker) for value/ROI narratives.
• Comfortable using AI-assisted research and data-enrichment tools for early-stage data gathering.
• Knowledge of financial/business-case modelling concepts (ROI, payback, TCO) is a plus.
• Familiarity with a retail data ecosystem (forecasting, scheduling, labor, inventory, store ops).
• Cloud experience with Azure, AWS, or GCP.

Responsibilities

• Pre-sale opportunity sizing: Gather public data on prospects and run early-stage value calculations to support pre-sales.
• Deeper value case development: Use prospect data to build defensible value cases with payback timelines and standards.
• Operational value insight: Interrogate live customer data to surface opportunities and operational insights.
• Usage and adoption insight: Assess platform usage and adoption and feed CX health views.
• Post-launch value realization: Partner with customers to measure value realized against the business case after go-live.

Skills

SQL

Python/R

ETL/ELT

Agile

English communication

Retail data (Desirable)

Education

Bachelor's degree in CS / Engineering / Data analytics

Tools

Power BI

Tableau

Looker

Azure

AWS

GCP

LLM-assisted research tools

Job description

Job Description

Job Summary

The Value Data Engineer sits within Logiles Customer Experience (CX) organization and provides the data engineering and analytics backbone behind every value conversation Logile has with a prospect or customer — from early-stage opportunity sizing during the sales cycle, through detailed business-case modelling, to evidenced ROI after go-live.

Logile does not run a separate Value Realization function, so this role is CXs custodian of value data: it owns the data, models and evidence base that make every value claim credible, working closely with the Account Manager and Customer Success Manager to ensure it is grounded in real customer and prospect data, consistent with Logiles Account Management Charter and the AM & CX partnership model.

Key Responsibilities

1. Pre-sale opportunity sizing: Gather publicly available data on prospects (sector, scale, format, geography), using AI-assisted research and data-enrichment tools to do this efficiently and at scale, and run early-stage, directional value calculations tied to the financial and business pressures Logiles platform addresses, to support the sales and pre-sales process.

1. Deeper value case development: Use prospect-provided data to develop a deeper, defensible value case, including detailed payback timelines, establishing and maintaining Logiles value methodology, workshops, baselines and business-case standards as CXs custodian of value data.

1. Operational value insight: Interrogate live customer system data to surface value opportunities and operational insight — including forecast accuracy, schedule effectiveness, labor productivity, production output and waste reduction.

1. Usage and adoption insight: Interrogate platform usage data to assess whether customers are using the full breadth of Logiles functionality, and using it effectively, feeding this into the CSMs adoption and customer health view.

1. Post-launch value realization: Partner directly with customers, alongside the CSM, to measure and evidence value realized against the original business case after go-live — supporting QBR reporting, renewal readiness and expansion conversations.

Key Relationships

• Relationship: Account Manager (incl. Pre-Sales)

  How they work together: Receives early-stage, directional value sizing to support pre-sales qualification, plus the evidenced value and ROI data that underpins renewal readiness, commercial risk visibility and expansion narratives.

  Cadence: Per opportunity / QBR / renewal cycle

• Relationship: Customer Success Manager

  How they work together: Supplies adoption, usage and operational-value data that feeds the CSMs customer health view, business reviews and expansion conversations.

  Cadence: Ongoing / weekly

• Relationship: Customer Support Manager

  How they work together: The roles main connection into the Product team: cross-references ticket and incident patterns with usage and value data, and channels pattern-level insight into Products roadmap conversations via the Customer Support Manager; supports QBR support inputs.

  Cadence: As needed / regular review

Skills & Experience

• Bachelors degree in computer science, engineering, data analytics, or commensurate work experience.
• 5-8 years of experience as a Data Engineer, Analytics Engineer, or similar role, ideally with some exposure to commercial, financial or value-analytics work.
• Strong SQL and Python/R; experience building and maintaining ETL/ELT pipelines against large structured and unstructured datasets.
• Writing scripts for statistical analysis, handling API requests from customer platforms, or executing predictive models.
• Experience with BI/analytics and dashboarding tools (e.g. Power BI, Tableau, Looker) to turn operational data into clear value and ROI narratives for commercial and customer-facing audiences.
• Comfortable using AI-assisted research and data-enrichment tools (e.g. LLM-based web research, enrichment platforms) to gather and structure public prospect data efficiently and accurately at the early sales stage.
• Working knowledge of financial or business-case modelling concepts (ROI, payback period, TCO) is a strong plus.
• Familiarity with a retail data ecosystem is a strong plus — forecasting, scheduling, labor, inventory, or store-operations data.
• Working experience with a cloud platform (Azure,AWS or GCP).
• Comfortable working directly with prospect- and customer-provided data under appropriate data-handling and confidentiality practices.
• Strong written and verbal communication skills, with the ability to present data-driven insight clearly to CX, GTM and customer stakeholders.
• Experience in Agile development environments.
• Proficiency in English and good verbal and written communication abilities.
• Experience in Retail store operations and P&L (Desirable)

Job Location & Schedule

• This is an onsite role at the Logile Bhubaneswar Office.
• The role supports Logiles EMEA CX team, so the selected candidate should expect flexible working hours with meaningful daily overlap with UK/EMEA business hours (typically GMT/BST), with occasional overlap into US hours for global accounts as needed.
• Standard shift: 1 PM – 10 PM IST (shift allowance applicable for non-standard shifts and as per role).
• Shifts starting after 4 PM: eligible for food allowance/subsidized meals and cab drop.
• Shifts starting after 8 PM: eligible for cab pickup as well.

Compensation and Benefits

• The compensation and benefits associated with this role is benchmarked against the best in industry and job location.
• Standard shift: 1 PM – 10 PM (shift allowance applicable for non-standard shifts and as per role).
• Shifts starting after 4 PM: eligible for food allowance/subsidized meals and cab drop.
• Shifts starting after 8 PM: eligible for cab pickup as well.