About the role
About the job: Senior Consultant Data Architecture & Engineering (GDC) | REMOTE
Work setup: remote, 5 p.m. to 2 a.m.
Job Highlights:
Competitive compensation package, salary, allowance, standard benefits including quarterly and annual performance-based cash bonuses, and other remuneration.
Leadership Opportunities: This role will help you extend and expand your knowledge and experience in technical leadership positions. These include technical decision-making; guidance and mentorship of more junior team members; and developing relationships with project, client, and company leadership, all while remaining hands-on in your areas of expertise.
Our technology focus is on Azure; you'll have plenty of exciting opportunities to grow your skills in Microsoft and Azure in an environment committed to technical excellence and client experience in a very specific, defined space. Six months of experience on our team is worth years somewhere else.
Microsoft Partnerships: Our great global relationship with Microsoft ensures that we have a pipeline of cutting-edge Azure work opportunities and access to the teams that have built the platform. You won't find this at other places.
Great working environment and company culture with a flexible work location.
Required Technical Skills:
At least 4 years of relevant experience
Expertise in designing and implementing logical and physical data models for cloud and hybrid data warehouse environments
Implementing data architectures to support a variety of data formats and structures, including structured, semi-structured, and unstructured data
Experience with multiple full life-cycle data warehouse implementations
Understanding of data architectures required to support data integration processing
Experience with data modeling technologies such as ER/Studio, ER/Win or similar
Experience with Microsoft Azure Data Platform services, including Azure Data Lake Store, Azure Storage, Azure Synapse, Azure Data Factory, Azure SQL database, Logic Apps, APIs
Demonstrated ability to quickly learn, adopt and apply new technologies
Data profiling and creation of source-to-target mappings
Ability to provision and configure Azure data service resources
Detailed Required Skills:
Python & SQL Scripting
SQL, PySpark
General Cloud Architecture competency capable of taking requirements and building out data pipelines
API Knowledge is required, but preference given to candidates who can create APIs
Preferred Skills/Certifications/Experience:
Microsoft Fabric
Microsoft Azure Cosmos DB, Data Flows, Express Route, Azure Active Directory
Experience creating strategies to migrate customers from on-premise environments to Azure
Power BI and semantic modeling
AWS Glue & Azure Data Factory
AWS S3 & Azure Blob
AWS Athena & Azure Databricks
AWS Redshift & Azure Synapse
AWS ECS & Azure AKS
Originally posted on Himalayas