Data Quality Engineer - Loyalty Platform

India·HyderabadFull-timemid

OtherData Quality Engineer

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Quick Summary

Overview

Key Responsibilities Data Cleansing and Profile Deduplication Audit customer profile data across loyalty platforms to identify duplicate, fragmented,

Technical Tools

OtherData Quality Engineer

Responsibilities

~1 min read

Audit customer profile data across loyalty platforms to identify duplicate, fragmented, or corrupted records
Design and execute profile merge logic using deterministic and probabilistic matching techniques
Develop and apply data cleansing routines to normalize, standardize, and enrich customer records
Document merge decisions, audit trails, and remediation outcomes for stakeholder review

Build and maintain automated validation pipelines to detect data sync failures, schema drift, and referential integrity violations across platforms
Develop scheduled reconciliation jobs that compare and validate records across mParticle, Braze, Xenial Beanstalk, GiveX, Snowflake, and Azure SQL
Implement alerting and reporting to surface data anomalies in near real-time
Own the end-to-end lifecycle of automated quality checks from design through deployment, monitoring, and iteration

Establish data quality KPIs and dashboards to track health metrics across the loyalty data ecosystem
Monitor platforms continuously for consistency, completeness, accuracy, and timeliness of data
Proactively identify and escalate data quality risks before they impact customer-facing loyalty experiences
Maintain runbooks and documentation for monitoring processes and remediation procedures

Validate data flows between loyalty platforms via REST APIs and event-driven pipelines
Perform integration testing to confirm data fidelity across ingestion, transformation, and consumption layers
Collaborate with engineers, system owners, and platform vendors to trace and resolve upstream data issues

5+ years of experience in data quality engineering, data engineering, or a directly related discipline
Proficiency in SQL with hands-on experience querying and manipulating data in Azure SQL and Snowflake
Demonstrated experience creating test scripts, test plans, and writing automation scripts and data pipelines in C# (.NET), Python, or both
Practical experience working with REST APIs for data validation and cross-system reconciliation
Proven experience with customer profile deduplication, identity resolution, or data cleansing at scale
Working familiarity with Azure cloud services and cloud-native data architectures
Ability to work independently, self-manage priorities, and deliver findings with minimal oversight

Experience with loyalty platforms, CDPs, or MarTech ecosystems, specifically mParticle, Braze, Xenial Beanstalk, GiveX
Familiarity with identity resolution concepts including deterministic and probabilistic matching
Experience building or operating data observability and monitoring frameworks
Background in QSR, retail, or high-volume consumer-facing platform environments
Knowledge of data privacy regulations (CCPA, GDPR) and consent management best practices

What We Offer

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Accellor is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic