About the Role
We are seeking a Data Architect & Engineer to design, implement, and optimize a modern cloud-based data platform using Google BigQuery and GCP-native tools. This role will be responsible for transforming raw data into high-quality, structured datasets following a Medallion Architecture (Bronze, Silver, Gold) to enable self-service analytics in Tableau and other BI tools.
You will drive data architecture, ELT strategy, streaming ingestion, real-time analytics, and performance optimization, ensuring that our BigQuery data warehouse is scalable, cost-efficient, and aligned with business intelligence needs.
Key Responsibilities
Architect & Implement BigQuery Data Transformations
- Design and implement scalable data pipelines using GCP-native tools to process data from Bronze (raw) → Silver (cleaned) → Gold (analytics-ready).
- Develop real-time and batch data pipelines using Dataflow, Apache Beam, and Pub / Sub for streaming and structured data ingestion.
- Optimize performance with BigQuery partitioning, clustering, materialized views, and optimized SQL transformations.
- Automate and schedule ETL / ELT workflows with dbt, Dataform, and Cloud Workflows.
Build & Maintain Fact and Dimension Tables
Define and manage fact tables (transactions, events, KPIs) and dimension tables (customers, providers, hospitals, products, locations).Implement Slowly Changing Dimensions (SCD) Type 1 and 2 for tracking data changes over time.Design pre-aggregated data marts optimized for low-latency BI queries in Tableau and Looker.Streaming & Real-Time Analytics
Develop streaming ingestion pipelines using Dataflow (Apache Beam), Pub / Sub, and Kafka.Enable event-driven transformations for real-time data processing.Ensure low-latency query optimization for real-time dashboards in Tableau, Looker, or Data Studio.Data Governance, Quality & Security
Implement schema validation, deduplication, anomaly detection, and reconciliation across multiple sources.Define access controls, row-level security (RLS), and column-level encryption to ensure data protection.Maintain data lineage and metadata tracking using Data Catalog and BigQuery Information Schema.Optimize & Automate Data Pipelines
Develop incremental data refresh strategies to optimize cost and performance.Automate data transformation workflows with dbt, Dataform, Cloud Composer (Apache Airflow), and Python.Monitor pipeline performance and cloud cost efficiency with Cloud Logging, Monitoring, and BigQuery BI Engine.Enable Self-Service BI & Analytics
Ensure that Gold Layer tables are structured for fast and efficient queries in Tableau, Looker, and self-service BI tools.Work with data analysts to optimize SQL queries, views, and datasets for reporting.Provide data documentation and best practices to business teams for efficient self-service analytics.Required Qualifications
Experience in Data Architecture & Engineering
5 years of experience in data engineering, cloud data architecture, or ELT development.Strong hands-on experience with Google BigQuery, SQL, and cloud-based data processing.Expertise in GCP & BigQuery Data Processing
Deep understanding of ELT / ETL principles, Medallion Architecture (Bronze, Silver, Gold), and Star / Snowflake schemas.Proficiency in dbt, Dataform, or SQL-based transformation tools for data modeling and automation.Experience with GCP services : BigQuery, Dataflow (Apache Beam), Pub / Sub, Cloud Storage, and Cloud Functions.BigQuery Optimization & Performance Tuning
Experience optimizing BigQuery partitioning, clustering, materialized views, and query performance.Expertise in cost-efficient query design and workload optimization strategies.Experience in Streaming & Real-Time Processing
Hands-on experience with streaming data pipelines using Dataflow (Apache Beam), Pub / Sub, or Kafka.Familiarity with real-time data transformations and event-driven architectures.Experience Supporting BI & Analytics
Strong knowledge of Tableau, Looker, and BI tools, ensuring Gold Layer tables are optimized for reporting.Ability to collaborate with data analysts and business teams to define data models and metrics.Bonus Skills (Preferred but Not Required)
Experience with LookML modeling in Looker.Knowledge of Cloud Composer (Apache Airflow) for data orchestration.Familiarity with AI / ML model deployment and data science pipelines in GCP.Why Join Us?
Lead a next-generation data platform built on Google BigQuery and GCP-native tools.Drive real-time data processing and self-service BI enablement in Tableau, Looker, and advanced analytics.Work with modern cloud-based technologies such as BigQuery, dbt, Dataflow, and Cloud Functions.Fully remote opportunity with a high-impact data engineering role.
