Senior AWS Cloud Data Architect

 
Vertical Relevance is looking for a Data Architect, to join our team as a full-time employee and work remotely. This person is responsible for the end-to-end planning, building, and deploying of software systems. Candidate will be able to drive the programming of well-constructed, testable code. 
As a Data Architect, you will implement technical solutions as part of a team for customer engagements. This role requires strong teamwork, communication, patience and organizational skills needed to drive customer success.    
At Vertical Relevance we deliver with excellence through teamwork, automating everything, constantly learning and taking ownership for the outcomes our customers experience.
Are you ready to join the team? 

Responsibilities 

• Help customers shape their journey to adopting the cloud and provide our customers with technical and strategic guidance on their “cloud journey”. 
• Consult, plan, design, and implement Data solutions on the cloud customers
  • Design AWS Data Lake implementations 
  • Database Migration to AWS Managed Services
  • Design and Develop AWS Data Quality and Governance solutions 
  • Become a deep technical resource that earns our customer's trust 
  • Develop high-quality technical content such as automation tools, reference architecture, and white papers to help our customers build on the cloud 
  • Innovate on behalf of customers and translate your thoughts into action yielding measurable results. 
• Support solution development by conveying customer needs and feedback as input to technology roadmaps. Share real world implementation challenges and recommend expansion of capabilities through enhanced and new offerings. 
  • Assist with technical briefs that document solutions 
  • Assist with reference architecture implementations 
• Support internal and external brand development through thought leadership: 
  • Work with Marketing/Alliances to write blog posts 
  • Work with Marketing/Alliances to develop internal case studies 

Qualifications  

• Professional experience architecting/operating Data / DevOps solutions built on AWS and Azure.
• Experience in software/technology customer facing experience. 

Sample Activities You’ll Do 
AWS Data Architecture and Data Lake Implementation
Assist Customer in building out a framework for data collection, data ingestion and catalog, data storage and data serving designed to optimize the efficiency in which information is accessed, curated, served and analyzed from up to two on-premises data sources. 

• Assist Customer with implementing Amazon Virtual Private Cloud (Amazon VPC), account, Amazon Simple Storage Service (Amazon S3) bucket strategy and capture impact for introducing critical data for a data lake.
• Assist Customer with achieving modern big data lambda architecture, providing an environment for consumption and utilization of data coming from either batch or streaming sources. 
• Assist Customer with defining detailed data architecture including raw data, conformed, structured, enriched, and aggregated.  

• Provide Customer general best practices in building production quality data pipeline for ingestion, transformation and consumption to downstream applications through a serving layer.  
• Assist Customer with defining details to data catalog and data serving layer through application program interfaces (APIs) if required.  
• Provide Customer general best practices for Amazon S3 data storage approach. 

Build Ingestion and Orchestration Ingestion
Based on Customer’s ingestion requirements provided. Assist Customer with building a reusable ingestion framework to onboard new data quickly based on one data source example. 

• Assist Customer with designing and building robust data ingestion solutions using monitoring, logging and alerting service with retry capabilities. 
• Assist Customer with server-less approaches where if applicable for the ingestion. 
• Assist Customer with building the framework for managing data updates to data stored in objects on Amazon S3. 

Orchestration
Based on Customer’s ingestion, orchestration and operational requirements. Provide general best practices to Customer for implementing an extensible and supportable orchestration framework for onboarding data to lambda architecture for a representative data source.  

• Advise Customer on leveraging AWS Services tools for data ingestion including Amazon Kinesis, Amazon EMR, AWS Lambda or other tool defined as part of the assessment. 
• Advise Customer on orchestration options on AWS Services including but not limited to AWS Glue, AWS Step Functions, AWS Batch, Amazon EMR, AWS Data Pipeline, AWS Lambda or other AWS native orchestration tooling. 
• Experience with Apache Iceberg Sagemaker, SageMaker Lakehouse, SageMaker Catalog, Terraform.
• Database migration factory 
• Aurora PostgreSQL
• Experience with Athena, Redshift, EMR, Glue, DataBricks and/or Snowflake.

• AWS Glue Data Catalog configuration and management.
• Python/PySpark for metadata automation.
• Data governance framework implementation.
• Metadata ingestion pipeline development.
• DCAM/DAMA framework experience.            
• Lake Formation security models.
• Enterprise taxonomy design.

• Assist Customer with building out the orchestration and state management processes to support data processing without data loss and exception and identify error handling. 
• Advise Customer on how the orchestration tooling will provide operational feedback to the support organizations in the event of a failure.  

Storage and Catalog Amazon S3 Data Storage Build 
Based on Customer’s usage requirements. Assist Customer with building the data lake storage approach for a representative data source. 

• Assist Customer with building data storage including buckets, prefixes, encryption, file types, partitioning. 
• Assist Customer with building automated data partition strategy. 
• Assist Customer with building Amazon S3 Bucket policies, logging and monitoring. 
• Assist Customer with building out data lifecycle management. 

• Assist Customer with building cross-region replication if required. 

Relevant Technical Tools 

• Primary Languages - Python
• Tooling, Services & Libraries – Airflow, Kafka, Parquet, Spark, Metaflow, Git, Hadoop 

Relevant AWS Services 

• AWS Infrastructure Scripting – CloudFormation, AWS CLI, AWS CDK 
• AWS Storage Services – S3 
• AWS Compute Services –  Lambda, Batch 
• AWS Database Services – RDS, DynamoDB, Redshift, Aurora, Neptune 
• AWS Networking Services – VPC 
• AWS Management and Governance Services – CloudTrail, Service Catalog 
• AWS Analytics Services – Athena, EMR, Kinesis, Glue, Lake Formation, Data Pipeline 
• AWS Security, Identity, Compliance Services – IAM 
• AWS Application Integration Services – Step Functions 

The Company 
Vertical Relevance was founded to help business leaders drive value through the design and delivery of effective transformation programs across people, processes, and systems. Our mission is to help firms at any stage of their journey develop custom solutions for success and growth. We provide a full range of services from strategy and design through to implementation and training. Our collective industry expertise is our greatest asset - our professionals have an average of 20+ years’ experience within Financial Services, across Wealth Management, Asset Management, Insurance, and Banking. Within our Customer Experience practice, we add complementary industry expertise (technology and media) synergizing the most relevant and successful customer trends. We focus wholly on your success by first rigorously assessing your business and technology challenges, and then right-sizing solutions that provide a meaningful ROI. With our industry experts hitting the ground running and focusing on nimble, quality delivery, we can see rapid, tangible improvements with our clients in productivity and effectiveness. When it makes sense for your company, we leverage our product partnerships in the areas of CRM, Sales Acceleration, Predictive Analytics, Digital Knowledge Management, and Cloud Transformation. 
Vertical Relevance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.