Value Data Engineer

About Logile

Logile is the leading retail labor planning, workforce management, inventory management and store execution provider deployed in thousands of retail locations across North America, Europe, Australia, and Oceania.

Our proven AI, machine-learning technology and industrial engineering accelerate ROI and enable operational excellence with improved performance and empowered employees. Retailers worldwide rely on Logile solutions to boost profitability and competitive advantage by delivering the best service and products at optimal cost.

From labor standards development and modeling to unified forecasting, storewide scheduling, and time and attendance, to inventory management, task management, food safety, and employee self-service — we transform retail operations with a unified store-level solution. Gain the Advantage with The Logic of Retail. One Platform for store planning, scheduling and execution.

For more information, visitwww.logile.com

Job Summary

The Value Data Engineer sits within Logile's 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 CX's 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 Logile's 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 Logile's 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 Logile's value methodology, workshops, baselines and business-case standards as CX's 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 Logile's functionality, and using it effectively, feeding this into the CSM's 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

The role is embedded in CX and works cross-functionally in support of the Account Management Charter's "one aligned customer narrative":

Relationship

How they work together

Cadence

Account Manager (incl. Pre-Sales)

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.

Per opportunity / QBR / renewal cycle

Customer Success Manager

Supplies adoption, usage and operational-value data that feeds the CSM's customer health view, business reviews and expansion conversations.

Ongoing / weekly

Customer Support Manager

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

As needed / regular review

Skills & Experience

• 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 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 Logile's 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.