Lead Data Architect

Company Description

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 rolewill establish architectural standards and best practices while providing pre-sales leadership for strategicopportunities.Key ResponsibilitiesDefine and drive the technical vision and roadmap for the Data Engineering CoEEstablish cross-cloud architecture standards and best practices with emphasis on Azure, GCP and AWSLead pre-sales activities for strategic opportunities, particularly AWS, Azure, GCP-focused clientsBuild the CoE's accelerator development frameworkMentor and guide pillar architects across all platformsDrive platform selection decisions and integration strategiesEstablish partnerships with key technology providers, especially CloudDefine governance models for the CoE implementationRepresent the organization as a technical thought leader in client engagements

Qualifications

12+ years of data engineering experience with 6+ years in leadership rolesDeep 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 frameworksProven track record of leading complex data platform implementationsStrong understanding of data governance, security, and compliance requirementsExperience building reusable frameworks and acceleratorsExcellent communication and stakeholder management skillsGoogle Cloud Professional Data Engineer certification preferred

Additional Information

Additional certifications in other cloud platforms (Azure, AWS) beneficialCloud Platforms: GCP (BigQuery, Dataflow, Dataproc), Azure (Synapse, ADF, Databricks), AWS (Redshift,Glue, EMR)Data Processing: Spark, Hadoop, Beam, FlinkData Warehousing: BigQuery, Snowflake, Synapse Analytics, RedshiftData Lake Technologies: GCS, ADLS Gen2, S3, Delta Lake, IcebergOrchestration: Cloud Composer, Airflow, Azure Data Factory, AWS Step FunctionsLanguages: Python, SQL, Scala, JavaInfrastructure as Code: Terraform, Pulumi, Bicep, CloudFormationDevOps: GitHub Actions, Azure DevOps, GCP Cloud Build, AWS CodePipelineData Modeling: dbt, Dataform, LookerCertifications: GCP Professional Data Engineer, Azure Data Engineer, AWS Data AnalyticsImpact ExpectationsEstablish the technical foundation for the CoE within the first 90 daysSupport pre-sales activities for a pipelineDefine and initiate development of 3-5 key accelerators for common data engineering patternsBuild credibility with strategic clients as a trusted technical advisor