Data Engineer - Reporting, Automation & Analytics Bengaluru, India

Britannica Home Fashions is looking for a Data Engineer - Reporting, Automation & Analytics to own the data pipelines, SQL storage, and reporting systems that power decision-making across our merchandising, inventory, and e-commerce teams.

In this role, you'll build and maintain Python data pipelines, SQL data lake storage, and QlikSense reports and dashboards used by teams across the business. You'll work directly with US-based stakeholders to turn ad hoc data requests into reliable, automated processes, and you'll be the person who tracks down why a number looks wrong and drives it to resolution.

We want someone who uses AI tools fluently as part of daily work, reaching for tools like Claude, Copilot, and ChatGPT to write and debug code, draft SQL, validate data, and build reports faster rather than doing everything by hand. As our technology platform evolves, you'll have opportunities to explore modern AI capabilities, intelligent automation, and next-generation reporting systems.

Data Pipelines & Automation

Design and build Python ETL pipelines to ingest, transform, and validate data from marketplace, inventory, and sales sources

Build and maintain SQL data lake storage so historical and change data stays available for analysis

Automate recurring data jobs (e.g., via Rundeck) and monitor them for failures and data anomalies

Use AI tools to accelerate pipeline development, script writing, and troubleshooting, and look for opportunities to automate manual, repetitive work

Build and maintain custom reports and dashboards in QlikSense/NPrinting for inventory, retail sales, and marketplace performance

Design and deliver fully custom, one-off data reports in response to stakeholder requests

Act as the point person for data confirmations, resolving mismatches between source systems and reports

Support and improve IT-enabled reporting systems, working with the broader tech team to keep them reliable and maintainable

Data Analysis & Quality

Investigate data discrepancies (e.g., UPC duplication, missing POs, PO/inventory mismatches) and drive them to resolution

Build anomaly detection and alerting for key business metrics such as new item launches, inventory changes, and ranking shifts

Amazon Seller/Vendor, Ads) to pull data into pipelines and reports

Database & Documentation

Design database schemas to support new and future systems

Document SQL schemas, pipeline logic, and report definitions so processes are maintainable beyond one person

Identify and implement improvements to existing data processes, reducing manual, repetitive work

Bachelor's degree or higher in Computer Science, Data Engineering, or a related field (or equivalent professional experience)

3+ years of experience in data engineering, analytics engineering, or a similar data-focused role
Strong SQL skills, including schema design for data warehouse or data lake use cases
Proficiency in Python for building and maintaining data pipelines and automation scripts
Hands-on experience with a BI/reporting tool (QlikSense preferred; Power BI, Tableau, or similar acceptable)
Experience integrating with REST APIs to pull and process third-party data
Fluent day-to-day use of AI tools to work faster on development, reporting, and troubleshooting
Strong problem-solving skills and meticulous attention to detail when reconciling data across systems
Able to work independently, manage multiple concurrent requests, and communicate clearly with non-technical, US-based stakeholders

Required - SQL (schema design, query optimization) - Python (ETL, automation scripting) - QlikSense / NPrinting or a comparable BI tool - REST API integration - Git and modern development workflows

Preferred (Nice to Have) - Backend software development experience (C#/.NET, Node, or Java) - Job scheduling and automation tools (Rundeck, Airflow, cron) - Docker, Azure, or AWS - AI-assisted development tools (GitHub Copilot, ChatGPT, Claude, etc.) - Experience with LLM integration, AI agents, or retrieval-augmented generation (RAG) - Familiarity with Model Context Protocol (MCP) for connecting AI applications with enterprise systems

We're looking for someone who enjoys turning messy, manual data work into clean, automated systems and owning reporting and data infrastructure end to end. The ideal candidate is curious about AI and automation, sharp at tracing a bad number back to its source, and comfortable moving across pipelines, reporting, analysis, and the occasional schema design.

You don't need experience with every tool listed. We're more interested in a strong foundation in SQL and Python, real fluency with AI tools to work faster and smarter, and a collaborative mindset.

On-site work: this position requires on-site presence in our Bengaluru office

Minimum experience: candidates must have at least 3 years of hands-on experience with SQL, Python, and data pipeline or reporting work

Bengaluru, India - full-time, on-site.

Our portfolio includes globally recognized brands such as UGG®, Koolaburra by UGG®, Pendleton®, Laura Ashley®, Forever 21®, and others.

~ Our technology team develops the systems that power our global business, from ERP platforms and business applications to automation, analytics, and system integrations.

Data Engineer (SQL, C#)

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