Data Engineer Loyalty & Customer Analytics

Experience: 3–5 years, including at least 2 years with cloud data platforms

Location: Mumbai / Hybrid. Must be available for a daily overlap of 2–3 hours with US Eastern Time for client meetings.

Role Summary

We are looking for a Senior Data Engineer to build the data foundation for a loyalty, credit card and customer lifecycle reporting transformation for a US fashion retail client.

The role brings together data from the client’s internal systems, its loyalty platform provider and its credit card partner. It matches customers across linked accounts and systems, and delivers clean, reliable reporting datasets for Power BI.

Key Responsibilities

Data integration

- Design, build and maintain ETL/ELT pipelines that integrate multiple internal and third-party sources, including sales transactions, loyalty platform data, credit card partner data and marketing systems, through databases, file transfers (SFTP) and APIs.
- Build and maintain customer identity matching: link and de-duplicate customers across linked accounts and systems and maintain the master customer ID mapping.

Data modeling and storage

- Design database schemas and dimensional models (fact and dimension tables), data marts and reporting layers optimized for Power BI.
- Develop stored procedures, views and transformations for business logic such as points balances, tier status, churn flags and purchase sequences.
- Build historical snapshots and slowly changing dimensions to track how tiers, points and rewards change over time.
- Build and maintain the retail fiscal calendar used across all reporting.

Automation and operations





- Schedule and orchestrate pipelines, monitor data loads, and troubleshoot failures, including Power BI dataset refresh issues.
- Optimize SQL and pipelines for performance on large transaction volumes, including pre-aggregated summary tables.

Data quality and governance

- Perform data profiling, validation and reconciliation across sources, and carry out root cause analysis of data issues.
- Implement automated data quality checks for duplicates, missing records and late or incomplete files.
- Handle customer personal data and payment-related data securely, following client data governance and privacy requirements.
- Create and maintain technical documentation, including the data dictionary and data lineage.
- Support UAT, production deployment and ongoing enhancements.

Required Skills

- Advanced SQL, query optimization and stored procedure development.
- Data warehousing and dimensional modeling (star schema).
- ETL/ELT development and pipeline orchestration.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP) and one cloud data warehouse (Snowflake, Redshift, Databricks or Microsoft Fabric/Synapse).
- Python or PySpark for data processing.
- Experience matching and de-duplicating customer records from multiple sources.




- Experience with large-volume transactional and structured or semi-structured data.
- Data quality management, validation and reconciliation.
- Experience supporting Power BI or similar reporting platforms, including scheduled refreshes.
- Strong logical thinking and problem-solving skills.

Preferred Technologies

- Snowflake, Amazon Redshift, SQL Server
- AWS (S3, Glue, Athena) or Azure equivalents (Data Factory, Data Lake, Fabric)
- Python / PySpark
- Apache Airflow or similar orchestration tools
- dbt (valuable to have)
- Git, JIRA / Azure DevOps

Preferred Domain Experience

- Retail or e-commerce analytics
- Loyalty and customer analytics
- CRM and customer engagement
- Banking, cards and financial services
- Marketing analytics

Good to Have

- Knowledge of loyalty and rewards programs, including member acquisition, tier management, and points accrual and redemption.
- Familiarity with loyalty KPIs such as active members, redemption rate, CLV, retention and churn.
- Experience integrating data from third-party loyalty platforms or credit card partners.
- Awareness of US data privacy regulations, such as CCPA.
- CI/CD practices for data pipelines.

Education

- Bachelor’s degree in engineering, Computer Science, Information Technology, Statistics, Mathematics or a related discipline.

Ideal Candidate

A hands-on Senior Data Engineer who has built cloud-based reporting data platforms from multiple sources and is comfortable solving customer matching and historical tracking problems. They take ownership of data quality, so the dashboards built on their work can be trusted.

📌 Data Engineer (Mumbai)
🏢 Lumina Datamatics
📍 Mumbai