DES - DE - Lead – Data Architect

Sutherland is seeking an attentive and goal-oriented person to join us as Data Architect We are a group of driven and hard-working individuals. If you are looking to build a fulfilling career and are confident you have the skills and experience to help us succeed, we want to work with you!

Lead the technical vision and strategy for the Data Engineering Center of Excellence across cloud platforms
(GCP, Azure, AWS), cloud-agnostic platforms (Databricks, Snowflake), and legacy systems. This leadership role
will establish architectural standards and best practices while 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 with emphasis on Azure, GCP and AWS
Lead pre-sales activities for strategic opportunities, particularly AWS, Azure, GCP-focused clients
Build the CoE's accelerator development framework
Mentor and guide pillar architects across 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

12+ years of data engineering experience with 6+ years in leadership roles
Deep expertise in Google Cloud Platform data services (BigQuery, Dataflow, Dataproc)
Strong knowledge of other cloud platforms (Azure Fabric/Synpase, 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 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

Cloud Platforms: GCP (BigQuery, Dataflow, Dataproc), Azure (Synapse, ADF, Databricks), AWS (Redshift,
Glue, EMR)
Data Processing: Spark, Hadoop, Beam, Flink
Data Warehousing: BigQuery, Snowflake, Synapse Analytics, Redshift
Data Lake Technologies: GCS, ADLS Gen2, S3, Delta Lake, Iceberg
Orchestration: Cloud Composer, Airflow, Azure Data Factory, AWS Step Functions
Languages: Python, SQL, Scala, Java
Infrastructure as Code: Terraform, Pulumi, Bicep, CloudFormation
DevOps: GitHub Actions, Azure DevOps, GCP Cloud Build, AWS CodePipeline
Data Modeling: dbt, Dataform, Looker
Certifications: GCP Professional Data Engineer, Azure Data Engineer, AWS Data Analytics

Impact Expectations
Establish the technical foundation for the CoE within the first 90 days
Support pre-sales activities for a pipeline
Define and initiate development of 3-5 key accelerators for common data engineering patterns
Build credibility with strategic clients as a trusted technical advisor