Data Architect

Responsibilities :

We are seeking a highly skilled and visionary Senior Data Architect with 15 plus years to design and implement a state-of-the-art data aggregation platform that captures, processes, and delivers insights from behavioral, analytics, and tracking data across multiple channels.

The platform will ingest real-time and batch data streams sourced from Client SDKs (Web, Mobile, Kiosk), Server-side events, and external partner systems.

As the Senior Data Architect, you will play a pivotal role in shaping the platform's architecture to provide a 360-degree view of customer behavior, supporting strategic decision-making and operational excellence. This position is ideal for individuals passionate about data ecosystems, medallion architecture, and cutting-edge tools for processing large-scale datasets.

Key Responsibilities

1. Strategic Data Architecture & Platform Design

Lead the design and conceptualization of a modern data aggregation platform aligned with the needs of behavioral tracking and analytics.

Establish a Medallion Architecture (Bronze, Silver, Gold) for capturing raw events, processing intermediate layers, and delivering clean, enriched datasets ready for analytics and downstream applications.

Design a scalable architecture capable of handling high-velocity data streams and batch processing with precision and efficiency.

Build and maintain reusable frameworks for data ingestion, transformation, and enrichment.

2. Real-Time & Batch Data Processing

Architect and implement real-time streaming pipelines to capture events from :

Client SDKs for Web, Mobile, and Kiosks.

Server-side events for key interactions.

Batch systems integrating data from surveys, delivery partners, and external data feeds.

Attribution data from marketing tools.

Create efficient mechanisms for schema validation, event enrichment, deduplication, and data storage across layers.

Define data retention policies and ensure high availability for both historical and live data.

3. Data Integration & Cross-Platform Enablement

Build seamless integration pipelines to harmonize disparate data sources and enable analytics-ready datasets.

Enable multi-channel data fusion for a unified view of customer interactions across online and offline touchpoints.

Integrate data pipelines with analytics, BI, and marketing platforms to drive actionable insights.

Utilize event-driven architectures to ensure real-time updates to customer profiles, behavioral scores, and predictive analytics.

4. Governance, Compliance & Data Quality

Define and enforce data governance best practices, including cataloging, lineage tracking, and quality monitoring.

Ensure the platform complies with data privacy regulations (e.g., GDPR, CCPA) and is designed for security-first operations.

Implement role-based access controls (RBAC), data encryption, and masking strategies to protect sensitive information.

Monitor and improve data quality metrics at every stage of the pipeline.

5. Advanced Data Modeling

Define and implement advanced data modeling techniques for transactional, analytical, and dimensional datasets.

Establish models that support customer profiling, time-series analysis, and attribution frameworks.

Enable flexible querying of large-scale datasets for diverse use cases, including customer segmentation, targeting, and behavioral analysis.

6. Leadership & Collaboration

Collaborate with engineering, product, analytics, and marketing teams to align data architecture with business goals.

Mentor junior team members, fostering a culture of excellence and innovation.

Communicate complex technical solutions to non-technical stakeholders and ensure buy-in from leadership.

Desired Skills & Qualifications :

Core Technical Expertise :

Data Architecture & Medallion Design : Expertise in building Bronze, Silver, and Gold layer architectures to optimize data flow, quality, and usability.

Real-Time Data Processing : Hands-on experience with streaming technologies such as Apache Kafka, Spark Streaming, Flink, Pulsar, or similar tools.

Batch Processing & ETL / ELT : Strong knowledge of data transformation frameworks such as Airflow, dbt, Prefect, Glue, or others.

Modern Data Warehousing : Expertise in cloud platforms like Snowflake, Databricks, BigQuery, or Redshift to implement scalable data lakes / warehouses.

Programming Skills : Proficiency in Python, SQL, Java, or Scala for data processing, modeling, and pipeline automation.

Data Modeling : Advanced understanding of dimensional modeling, NoSQL, and normalized structures.

Behavioral & Analytics Data Expertise :

Experience working with Customer Data Platforms (CDPs) and downstream analytics / attribution tools (Braze, Branch, Amplitude, Treasure Data, Marigold).

Proven ability to design solutions for behavioral tracking, customer analytics, and event-based architectures.

Knowledge of tools and frameworks for customer attribution modeling, user journey analytics, and campaign effectiveness measurement.

Data Governance & Compliance :

In-depth knowledge of data governance frameworks, including metadata management, privacy-first architectures, and compliance mandates (GDPR, CCPA etc.).

Proven ability to establish processes for data quality monitoring and error handling in large-scale environments.

Industry Knowledge :

Experience in industries like Quick Service Restaurants (QSR), e-commerce, or consumer analytics is preferred.

Familiarity with high-volume, low-latency systems that serve millions of daily active users.

Benefits of Joining :

Impactful Role : Lead the development of a next-generation data platform that will serve as the backbone of critical business insights.

Innovative Environment : Work with cutting-edge tools and frameworks in a fast-paced, data-driven organization.

Growth Opportunities : Collaborate with cross-functional teams, mentor peers, and drive large-scale data initiatives.