Lead Data Architect

As a Data Architect at Sutherland, you will be responsible for leading the technical vision and strategy for the Data Engineering Center of Excellence. Your role will involve working across cloud platforms such as GCP, Azure, AWS, cloud-agnostic platforms like Databricks and Snowflake, and legacy systems. Your leadership will be crucial in establishing architectural standards, best practices, and providing pre-sales leadership for strategic opportunities. **Key Responsibilities:** - Define and drive the technical vision and roadmap for the Data Engineering CoE - Establish cross-cloud architecture standards and best practices focusing on Azure, GCP, and AWS - Lead pre-sales activities for strategic opportunities, particularly for AWS, Azure, and GCP-focused clients - Build the CoE's accelerator development framework - Mentor and guide pillar architects on all platforms - Drive platform selection decisions and integration strategies - Establish partnerships with key technology providers, especially Cloud - Define governance models for the CoE implementation - Represent the organization as a technical thought leader in client engagements **Qualifications:** - 12+ years of data engineering experience with 6+ years in leadership roles - Deep expertise in Google Cloud Platform data services such as BigQuery, Dataflow, Dataproc - Strong knowledge of other cloud platforms like Azure Fabric/Synapse, Data Factory, AWS - Extensive experience with modern data architecture patterns and frameworks - Proven track record of leading complex data platform implementations - Strong understanding of data governance, security, and compliance requirements - Experience in building reusable frameworks and accelerators - Excellent communication and stakeholder management skills - Google Cloud Professional Data Engineer certification preferred - Additional certifications in other cloud platforms (Azure, AWS) beneficial The company also works with Cloud Platforms like GCP (BigQuery, Dataflow, Dataproc), Azure (Synapse, ADF, Databricks), AWS (Redshift, Glue, EMR). Data Processing technologies include Spark, Hadoop, Beam, Flink, Data Warehousing solutions like BigQuery, Snowflake, Synapse Analytics, Redshift, Data Lake Technologies such as GCS, ADLS Gen2, S3, Delta Lake, Iceberg, Orchestration tools like Cloud Composer, Airflow, Azure Data Factory, AWS Step Functions, Languages including Python, SQL, Scala, Java, Infrastructure as Code tools like Terraform, Pulumi, Bicep, CloudFormation, DevOps tools like GitHub Actions, Azure DevOps, GCP Cloud Build, AWS CodePipeline, Data Modeling solutions such as dbt, Dataform, Looker, and Certifications like GCP Professional Data Engineer, Azure Data Engineer, AWS Data Analytics. If you are looking to establish the technical foundation for the CoE, support pre-sales activities, and initiate development of key accelerators for data engineering patterns, then this role at Sutherland might be the perfect fit for you. As a Data Architect at Sutherland, you will be responsible for leading the technical vision and strategy for the Data Engineering Center of Excellence. Your role will involve working across cloud platforms such as GCP, Azure, AWS, cloud-agnostic platforms like Databricks and Snowflake, and legacy systems. Your leadership will be crucial in establishing architectural standards, best practices, and providing pre-sales leadership for strategic opportunities. **Key Responsibilities:** - Define and drive the technical vision and roadmap for the Data Engineering CoE - Establish cross-cloud architecture standards and best practices focusing on Azure, GCP, and AWS - Lead pre-sales activities for strategic opportunities, particularly for AWS, Azure, and GCP-focused clients - Build the CoE's accelerator development framework - Mentor and guide pillar architects on all platforms - Drive platform selection decisions and integration strategies - Establish partnerships with key technology providers, especially Cloud - Define governance models for the CoE implementation - Represent the organization as a technical thought leader in client engagements **Qualifications:** - 12+ years of data engineering experience with 6+ years in leadership roles - Deep expertise in Google Cloud Platform data services such as BigQuery, Dataflow, Dataproc - Strong knowledge of other cloud platforms like Azure Fabric/Synapse, Data Factory, AWS - Extensive experience with modern data architecture patterns and frameworks - Proven track record of leading complex data platform implementations - Strong understanding of data governance, security, and compliance requirements - Experience in building reusable frameworks and accelerators - Excellent communication and stakeholder management skills - Google Cloud Professional Data Engineer certification preferred - Additional certifications in other cloud platforms (Azure, AWS) beneficial The company also works with Cloud Platforms like GCP (BigQuery, Dataflow, Dataproc), Azure