Support Account Executives to Design Prospect Solutions.
Estimate Level of Effort for Proposed Solutions and Author Technical Aspects of SOWs to submit proposals to Customers.
Design solutions that allow us to keep our customers’ data separate and secure to meet compliance and regulatory requirements.
Design, Build, and Operate the infrastructure required for optimal data extraction, transformation, and loading from a wide variety of data sources using SQL, cloud (mainly AWS) migration, and ‘big data’ technologies.
Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operation problems.
Design, Build, and Operate large, complex data lakes that meet functional / non-functional business requirements.
Optimize the ingestion, storage, processing, and retrieval of various data types, from near real-time events and IoT to unstructured data such as images, audio, video, documents, and others.
Use Jupyter Notebooks to build and deploy ML models.
Leverage AWS AI/ML pre-built solutions to accelerate customer work.
Work with customers and internal stakeholders, including the Executive, Product, Data, Software Development, and Design teams, to assist with data-related technical issues and support their data infrastructure and business needs.
Manage the Delivery Solutions Architects.
Be a point of contact for Escalations from the Delivery Solutions Architects and Enable a Process to ensure their work and commitments are delivered as intended.
Understand the customer’s data & analytics requirements and translate them into system / technical requirements.
Provide exceptional AWS technical design and thought leadership.
Lead technical workshops and advise customers on architectural and strategic data decisions.
Ensure success in designing, building, and migrating data and analytics services on the AWS platform.
Educate customers on best practices to ensure their solutions are designed for successful deployment in the cloud.
Work with other AllCloud teams to ensure quality and customer success
Capture and share knowledge with AllCloud’s broader technical experts community
Provide pre-sales architecture support to drive sales and complete cloud architectural activities and engagements.
Employees and direct managers will work to outline a personal development plan for the calendar year, identifying specific focus areas and personal development objectives that must be met.
Requirements
We seek a candidate with 5+ years of experience in a Data Scientist/Machine Learning Engineer role who has attained a Bachelor's (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems, or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Spark, ElasticSearch, Hadoop, Kafka, Kinesis, etc.
Experience with relational SQL and NoSQL databases, such as MySQL, Postgres, DynamoDB, or Cassandra.
Experience with AWS cloud services: EC2, RDS, EMR, Redshift etc.
Experience with functional and scripting languages: Python, Java, Scala, etc.
Experience with various ML models for classification, scoring, and more.
Experience with Deep Learning Neural Networks (Convolution, NLP etc.).
Experience with AWS AI/ML Services.
Experience with Python coding.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with various databases.
Experience building and optimizing big data pipelines, architectures, and data sets.
Strong analytic skills related to working with unstructured datasets.
A strong understanding of AWS Infrastructure, including EC2, Lambda, VPC, EKS, S3, and others, is required to support data projects.
Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Experience supporting and working with external customers in a dynamic environment.