Job Description: Data Architect

We are seeking an experienced and hands-on Data Architect to design, develop, and optimize scalable, secure, and high-performance data platforms. The ideal candidate will have strong expertise in data architecture, cloud data engineering, data integration, and analytics, with hands-on experience in Google Cloud Platform (GCP), BigQuery, and Dataflow.

The candidate will be responsible for defining data architecture strategies, building and optimizing data pipelines, implementing data governance standards, and enabling data-driven decision-making. The role requires a combination of strategic architectural expertise, technical leadership, and hands-on problem-solving skills.

Key Responsibilities:

- Design and implement scalable, secure, and high-performance data architectures across cloud environments.

- Architect and manage cloud-based data platforms using GCP, BigQuery, and Dataflow.

- Design, develop, and optimize ETL/ELT pipelines and data integration workflows using Python, Apache Airflow, dbt, and cloud-native services.

- Develop and manage data processing solutions using Google Cloud Dataflow for batch and streaming workloads.

- Design and optimize data warehouses, data models, and analytical solutions using BigQuery, Snowflake, and Azure Synapse.

- Implement data ingestion, transformation, orchestration, and integration solutions across multiple data sources.

- Develop and optimize SQL queries, stored procedures, data models, and database performance.

- Build and maintain interactive dashboards and analytical reports using Power BI.

- Establish data quality, governance, security, metadata management, and compliance standards.

- Collaborate with business stakeholders, data engineers, BI developers, and analytics teams to define and execute the data architecture roadmap.

- Identify architectural gaps, troubleshoot production issues, and implement solutions to improve data reliability, scalability, and performance.

- Provide technical leadership, architectural guidance, and best practices for data engineering and analytics teams.

- Explore and integrate AI/ML capabilities into modern data platforms to enable advanced analytics and business insights.

- Maintain technical documentation, architecture diagrams, data models, and implementation standards.

Required Skills and Qualifications:

- 8+ years of experience in Data Architecture, Data Engineering, Business Intelligence, or related roles.

- Strong hands-on experience in Google Cloud Platform (GCP), BigQuery, and Dataflow.

- Proven experience designing and implementing enterprise-level data architectures and cloud-based data solutions.

- Strong knowledge of BigQuery data modeling, partitioning, clustering, query optimization, and cost management.

- Hands-on experience with Dataflow for batch and streaming data processing.

- Proficiency in Python, SQL, and data pipeline development.

- Experience with Apache Airflow and dbt for workflow orchestration, data transformation, and automation.

- Strong understanding of ETL/ELT processes, data integration patterns, and distributed data processing.

- Experience with Snowflake, Azure Synapse, and Azure Data Factory is an added advantage.

- Knowledge of Microsoft SQL Server, T-SQL, stored procedures, database design, and performance tuning.

- Experience with Power BI, including data modeling, dashboard development, and performance optimization.

- Understanding of data governance, data quality, security, metadata management, and cloud architecture best practices.

- Familiarity with AI/ML concepts and their integration with modern data platforms.

- Strong analytical, problem-solving, communication, and stakeholder-management skills.

- Ability to work independently, manage priorities, and provide hands-on technical support in a dynamic environment.

Primary Skills:

- Data Architecture, Google Cloud Platform (GCP), BigQuery, Google Cloud Dataflow, Python, SQL, Data Engineering

Secondary Skills:

- Snowflake, Apache Airflow, dbt, Azure Data Factory, Azure Synapse, Microsoft SQL Server, Power BI, ETL/ELT, Data Modeling, Data Governance, Cloud Data Integration