Data Analytics Architect

Department/Project Description

We are a global audience and location intelligence company that helps marketers connect the digital and physical world. We provide data-driven solutions to enhance marketing campaigns by leveraging location and audience data to reveal consumer behavior and enable more precise targeting and measurement. We work on high-end / high-performance / high-throughput systems for in-time analysis of data for autonomous driving and other big data applications e.g. for E-commerce.



Job Responsibilities

We are looking for a Data Analytics Architect to join our technical proficiency track. This is a highly technical, Individual Contributor (IC) role. You will act as the Technical Lead for your squad—making critical architectural decisions, defining engineering standards, and driving cross-squad collaboration—without the responsibilities of people management.

You will be the technical north star for the team, approaching extremely complex data problems with a rigorous software engineering mindset. You will design, build, and oversee production-grade data platforms that process massive volumes of geo-spatial data, audience attributes, and geo-location time-series data.


Job Description

7+ years of experience in Data Engineering, Analytics Engineering, or Backend Development with a deep focus on massive data systems.
 

Geo-Spatial & Time-Series Expertise: Proven, hands-on experience handling massive datasets specifically involving geo-spatial (GIS) data, audience attributes, and high-frequency time-series data.
 

Advanced Software Engineering (Python): Mastery of Python beyond standard data scripting. You write highly modular, object-oriented code. You have deep, practical experience with Test-Driven Development (TDD), mocking, exception handling, and performance profiling, functional programming.
 

Architectural Vision: Deep expertise in designing scalable data architectures using both relational and horizontally scalable data warehouses/lakehouses (e.g., Snowflake, Redshift, Athena, StarRocks, Iceberg). You deeply understand query execution plans, partitioning, clustering, and cloud cost governance.
 

Big Data Frameworks: Extensive experience with large-scale data processing frameworks (e.g., Apache Spark, PySpark, AWS EMR, Glue) to handle massive throughput.
 

Expert SQL & dbt: You design scalable, robust data models (using Jinja, macros, incremental strategies) that serve as the foundation for our entire analytics layer.
 

AWS Cloud Native & IaC: Hands-on experience building architectures in AWS (e.g.: AWS Lambda, AWS Batch, Glue, StepFunctions, S3, EC2, ECS, ECR, Fargate) and deploying them using Infrastructure as Code (Terraform).
 

Leadership Skills: Superb organizational and communication skills. You can distill complex architectural trade-offs for non-technical stakeholders and drive technical consensus among your engineering peers.