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!

Job Description

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

Qualifications

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 Information

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