Senior Data Architect
EffectualSalary not specified
Full Time
Expert & Leadership (9+ years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Data ManagementIndustries
Requirements
Candidates should possess 8+ years of experience in software development, specifically within data engineering, data warehousing, or data analytics companies and teams. They must have expertise in designing and implementing complex, scalable data pipelines and ETL services, along with expert-level proficiency in Python, Java, and Typescript. Furthermore, they require extensive experience with cloud-based data storage and processing technologies, particularly AWS services such as S3, Step Functions, Lambda, and Airflow, and a deep understanding of Lake House architecture.
Responsibilities
As a Senior Platform and Data Lake Engineer, you will be responsible for designing, developing, and optimizing data lake solutions to support scientific data pipelines and analytics capabilities, as well as designing and architecting services to meet customer data processing needs. You will also implement data quality and governance frameworks to ensure data integrity and compliance, and work closely with cross-functional teams to ensure the seamless ingestion, processing, and storage of significant volumes of scientific data within the Databricks platform.
Skills
Data Lake
Data Pipelines
Databricks
Cloud
AI
Data Infrastructure
Data Ingestion
Data Processing
Data Storage
Analytics
TetraScience
Cloud platform for scientific data management
About TetraScience
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.
Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees
Benefits
Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements
Risks
Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.
Differentiation
TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.
Upsides
Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.
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