Mindlance
Data Platform Engineer
Mindlance, Charlotte, North Carolina, United States, 28245
Job Descriptions:
In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering.Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Provide expertise to client senior leadership on innovative Engineering business solutions.Strategically engage with client personnel.Required Qualifications:
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education..Looking for Production Platform Engineers to support and build production platforms. DO NOT send resumes of Data Scientists as they will not be rejected.Participate in developing Generative AI Platform CapabilitiesResponsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure Client)Participate in day-to-day standups for platform capability builds.Research industry best practices, evaluate new technologies, develop standards and engineering best practices and recommend innovative solutions that support automation and improve platform resiliency and fault tolerance of critical applications.Execute on roadmaps that align with technology and business strategy. Perform hardware and capacity planning, analysis, and forecasts for your portfolio of applications with focus on highest availability, scalability, performance, and timely delivery.Act as an expert resource for other technical teams within DTISupport of all on-prem Production infrastructure and cloud platforms including support of end users.5+ years of Python experience5+ years of big data experience needed (Big Query, Hadoop)5+ years with Linux O/S capabilities3 years of experience in AIML area (MLOps)3 + years of supporting cloud infrastructures (GCP/Azure) as well as some experience building complex infrastructure programmatically with IaC tools (Terraform/Ansible etc.)3+ years of Pyspark experience3+ years with Client Virtualization technologiesWorking knowledge of Auto Client technologies such as H2O Driverless AI, DataRobot, VertexAI, Elastic and Vector DBExcellent verbal, written, and interpersonal communication skills. Ability to articulate technical solutions to both technical and business audiences.Recent and demonstrated ability to influence management on technical or business solutions.Working knowledge of design and build grid computing with CPU and GPU supporting AIML and NLPWorking knowledge of high-performance storage technologies along with Object StorageKnowledge and understanding of network infrastructure to support high throughput and low latency grid computing.
In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering.Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Provide expertise to client senior leadership on innovative Engineering business solutions.Strategically engage with client personnel.Required Qualifications:
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education..Looking for Production Platform Engineers to support and build production platforms. DO NOT send resumes of Data Scientists as they will not be rejected.Participate in developing Generative AI Platform CapabilitiesResponsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure Client)Participate in day-to-day standups for platform capability builds.Research industry best practices, evaluate new technologies, develop standards and engineering best practices and recommend innovative solutions that support automation and improve platform resiliency and fault tolerance of critical applications.Execute on roadmaps that align with technology and business strategy. Perform hardware and capacity planning, analysis, and forecasts for your portfolio of applications with focus on highest availability, scalability, performance, and timely delivery.Act as an expert resource for other technical teams within DTISupport of all on-prem Production infrastructure and cloud platforms including support of end users.5+ years of Python experience5+ years of big data experience needed (Big Query, Hadoop)5+ years with Linux O/S capabilities3 years of experience in AIML area (MLOps)3 + years of supporting cloud infrastructures (GCP/Azure) as well as some experience building complex infrastructure programmatically with IaC tools (Terraform/Ansible etc.)3+ years of Pyspark experience3+ years with Client Virtualization technologiesWorking knowledge of Auto Client technologies such as H2O Driverless AI, DataRobot, VertexAI, Elastic and Vector DBExcellent verbal, written, and interpersonal communication skills. Ability to articulate technical solutions to both technical and business audiences.Recent and demonstrated ability to influence management on technical or business solutions.Working knowledge of design and build grid computing with CPU and GPU supporting AIML and NLPWorking knowledge of high-performance storage technologies along with Object StorageKnowledge and understanding of network infrastructure to support high throughput and low latency grid computing.