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Senior Data Architect & Engineer (BigQuery & GCP Analytics)

Full-Time

Remote

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Overview:

We are seeking a Senior 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.