Job Summary:

• Work with product, data scientists, and roboticists to build visualization tools and dashboards.
• Build and maintain cloud pipelines for components of ML applications such as Data ingestion, model training and deployment.
• Build solutions to satisfy the data management and data versioning needs of Blue River.
• Connect ecosystem by building integrations across multiple existing and new tools
• Implement and optimize data models, queries, and ETLs for complicated text, image, and sensor data
• Design service-level interfaces for ML and Data Platform
• Build and design Data Warehouse and procedures
• Build and own operations, performance and optimization of BI platforms
• Be the conduit between the data platform engineering team and the data science/analytics/ insights team
• Wear different hats within the data domain as a data engineer, a reports developer and a business analyst
• Build and own instrumentation to ensure secure data collaboration and increased ease of discovery

Skills on Resume: 

• Data Engineering (Hard Skills)
• Cloud Technologies (Hard Skills)
• Data Visualization (Hard Skills)
• Database Management (Hard Skills)
• Integration (Hard Skills)
• Machine Learning Fundamentals (Hard Skills)
• Data Governance (Hard Skills)
• Collaboration (Soft Skills)

Job Summary:

• Create Big Data and cloud ETL Solutions with high volumes and a variety of vehicle sensor ingest data from business applications and machines.
• Collaborate with other technology teams to implement a framework of tools and technologies to ingest a high volume of data to support data science and Self-Driving machine learning activities.
• Solve complex analytical requirements using software engineering tools.
• Implement tools and technologies to provide data governance such as data catalog and lineage.
• Used case-based implementation of AWS RDS, Elastic Search, Graph Databases, Time Series Databases, and NOSQL DBs.
• Create data applications with the ability to do searches, real-time data alerts, and APIs to pull the data on a large volume of data.
• Build data applications to provide real-time data alerts & high throughput analytics.
• Automate pipelines with Airflow, KubeFlow and/or SageMaker.
• Manage Ingest Search Data Lake ingest and access.
• Assist in setting governance models for data preparation and quality assurance with 3rd parties
• Stay current on industry trends and data technologies
• Build PowerBI reports and associated semantic data layer as per business specifications

Skills on Resume: 

• Big Data ETL Solutions (Hard Skills)
• Collaboration (Soft Skills)
• Analytical Problem Solving (Hard Skills)
• Data Governance (Hard Skills)
• Database Technologies (Hard Skills)
• Data Application Development (Hard Skills)
• Pipeline Automation (Hard Skills)
• Power BI Reporting (Hard Skills)

Job Summary:

• Building and operating a data lake including the setup, configuration and monitoring of platform services, ensuring a suitable level of performance is provided to consumers, unlocking data potential for the business
• Designing, planning, implementing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments
• Work according to professional engineering practices, including Internet protocols, coding standards and reviews, source control management, design and operations processes following site reliability engineering principles
• Contribute to the continuous improvement of the wider IT&S team by supporting and coaching Platform Engineers and proactively improving the quality standards and efficiency of delivery.
• Advocate and lead in this and promote a culture of security and compliance in everything that we do.
• Build out Apache Spark ETL data pipelines in Azure Databricks to ingest, transform, enrich, aggregate, and share structured and unstructured clinical data from large medical institutions into a clinical data repository for standardized HIPAA-compliant access to customer data.
• Work with Data Scientists to implement, maintain, and prototype statistical, machine learning, and NLP models to enrich datasets.
• Assist Clinical Intelligence to develop and maintain clinical ontologies to define relationships between different entities.
• Provide the capability for internal teams to harness data to create and discover meaningful insights resulting in positive outcomes in improved care for patients and decreased provider fatigue.

Skills on Resume: 

• Data Lake Management (Hard Skills)
• Infrastructure Design (Hard Skills)
• Professional Engineering Practices (Hard Skills)
• Team Coaching (Soft Skills)
• Security Advocacy (Soft Skills)
• Apache Spark ETL Development (Hard Skills)
• Collaboration with Data Scientists (Soft Skills)
• Clinical Ontology Development (Hard Skills)