Lead Consultant Data Architecture & Engineering (GDC) - WFH, Midshift

About the job: Lead 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 experience leading small- to medium-sized technical teams (this includes work allocation/distribution to team members, technical escalation and support, and representing the team in Agile ceremonies and client meetings). - 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 skillset—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