Vrdm Technologies

Key Responsibilities

Data Quality Engineering

•      Define and own the QE strategy for data assets including customer, product, inventory, transaction, and behavioral event data

•      Design and implement data validation frameworks covering completeness, accuracy, consistency, timeliness, and referential integrity

•      Lead testing of ETL/ELT pipelines, data lake and warehouse layers (raw, curated, consumption), and real-time streaming pipelines

•      Establish data contract testing practices between producing and consuming systems

•      Build automated data quality monitors and alerting that operate continuously in production environments

•      Partner with data governance and data stewardship teams to align QE standards with enterprise data policies

eCommerce Platform Integration Testing

•      Test integrations between the eCommerce platform and downstream data consumers including CDP, CRM, marketing automation, and analytics tools

•      Validate real-time personalization pipelines for homepage, PDP, cart, and post-purchase experiences

•      Ensure data quality for key eCommerce events: product views, add-to-cart, checkout, order confirmation, returns, and search queries

Cross-Functional Partnership

•      Collaborate with data scientists, data engineers, product managers, and business analysts to define acceptance criteria for data and AI deliverables

•      Champion a culture of data quality ownership across data producers and consumers in the eCommerce organization

Qualifications

Required

•      7+ years in data or quality engineering, with at least 2 years leading a team or technical discipline

•      Proven experience testing data pipelines (batch and streaming) across modern data stack technologies (Spark, Kafka, Airflow, dbt, Snowflake, BigQuery, Databricks, or similar)

•      Hands-on experience with Martech and Personalization space is a must.

•      Strong SQL skills and proficiency in Python for data validation scripting and test automation

•      Familiarity with eCommerce data domains: customer behavior, product catalog, order management, inventory, and digital marketing