ElevateBio is a cell and gene therapy technology company built to power the development of transformative cell and gene therapies today and for many decades to come. The company has assembled industry-leading talent, built world-class facilities, and integrated diverse technology platforms necessary for rapid innovation and commercialization of cell, gene, and regenerative therapies.
ElevateBio is seeking Cloud Data Architect to develop, design and deliver innovative solutions for our organization’s Data Analytics and Data Science platform, strategy, processes, and systems from ground zero. Our company is building data solutions, AI-enabled capabilities in our cloud based infrastructure across our core offering areas in cell and gene therapy R&D and Manufacturing. We are looking for a technical leader who can drive the design, development and operations of complex data systems and cloud engineering processes. This individual will be responsible for partnering across all scope of solutions, establish KPIs, a mindset of continuous improvement, performance in accordance with industry standards and cost effectiveness of the data solutions. In addition, this individual will partner with cross-functional leaders to innovate on a regular basis while providing direction, support, leadership, and transforming AI-specific technology requirements into fit for purpose business solutions.
The Cloud Data Architect will provide sound operational, technical and process leadership as ElevateBio seeks to grow its presence across the globe. We are seeking an individual with an established record of contributions with advanced information technology, leadership, and artificial intelligence skills leading to improved technology roadmap, heightened process efficiency and enhanced internal controls. In addition, the role requires a hands-on, can-do attitude, the ability to juggle technology requirements with demands of a growing organization, and network with broader IT community outside the organization.
This position will have a broad range of responsibilities, including cross-functional partnership with IT team and science groups. The role includes following key responsibilities:
- Cloud Infrastructure Development, Delivery and Support across THREE key areas
o Artificial Intelligence, Data Science, and Statistical Computing
o Computational Biology and Translational Science
o IT Requirement Analysis, Business Intelligence, and Cloud
- Lead architecture, design and development of end to end Cloud based solutions with heavy focus on application, data warehouse and business intelligence solutions with good understanding of infrastructure
- Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platform
- Define and execute strategy on building data storage infrastructure, data pipelines, data warehouses, data lakes, data APIs and self-service tooling for diverse types of data (structured and unstructured), and diverse workloads/dataflows (transactional, analytics, ML pipelines, research data science)
- Design, develop, and implement end-to-end data solutions (storage, integration, processing, access)
- Identify strategic data requirements of the enterprise, how data is stored, and assess the enterprise’s internal and external data and design blueprint to manage the available data
- Create inventory of enterprise’s data, store data in easily accessible format, design and develop complex database management systems and separate public data from private ones
- Collaborate with cross-functional leaders to create data models in line with the organizations need, research to collate new data and update the company’s database from time to time
- Create back up plan to cater for the data needs of the company in times of emergency or cyber attack
- Meld existing data architecture with new ones as technology emerges, learn latest techniques for data modeling and management, and ensure the protection of data from unauthorized persons
- Propose architectures that consider cost/spend in AWS/Snowflake and develop recommendations or plans to right-size AWS/Snowflake data infrastructure
This individual will have a significant role in designing the roles and functions which are expected to grow over time and future information technology capabilities like:
- Artificial Intelligence and Predictive Analytics
- Enterprise Data Architecture strategy
- Bioinformatics and Data Analytics
- 7+ years of data architecture, engineering, database management, data analytics, Data warehousing, including cloud-native database and modern data warehouse (snowflake)
- 5+ years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Hadoop, MySQL, Snowflake, PostgreSQL, Redshift, Azure SQL Warehouse, etc.)
- Experience designing and building solutions utilizing various Cloud services such as EC2, S3, EMR, Kinesis, RDS, Redshift/Spectrum, Lambda, Glue, Athena, API gateway, etc
- Experience serving as an architect for data solutions on Amazon Web Services/Snowflake
- Advanced knowledge of modern data architectural patterns, standards and data governance in relational and nonrelational databases
- Deep experience designing and deploying end to end solutions with a cloud platform’s analytic services.
- Proficiency in data migration and processing using AWS services e.g., VPC/SG, EC2, S3, AutoScaling, CloudFormation, LakeFormation, DMS, RDS, Aurora, Cloudtrail, CloudWatch, Docker, Lambda, Glue, Sage Maker, API GW
- Hands-on development using and migrating data to cloud platforms
- Proficiency in relational database design and development
- Proficiency and hands-on experience with big data technologies
- Experience in languages such as SQL, Python, Java, Scala, and/or Go
- Proficiency with both Linux and Windows
- Familiarity with standard industry tools for data cataloging, data ingestion, capture, processing and curation e.g., Snowflake, Kafka, Collibra, Map Reduce, Hadoop, Spark, Flume, Hive, Impala, SparkSQL.
- Familiarity with Data Analytics, AI, and Machine learning systems and how they integrate into enterprise business process applications is desirable
- Analytical approach to problem-solving; ability to use technology to solve business problems
- Passionate about learning new technologies
- Bachelor’s degree (B.S. equivalent) preferably in Computer Science, Data Science,Mathematics, Engineering or a related field is a must
- Masters or PhD in Computer Science, Engineering or Math is preferred
- AWS and /or Snowflake Platform Certification preferred.