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What You Will Contribute to Altos

The Altos Scientific Computing and Data team is seeking a Data and Platform engineer to scale our scientific data and metadata management capabilities. As a Data Engineer, you will be responsible for developing and maintaining efficient data pipelines and processes to transform, migrate, and integrate data and metadata across various scientific systems - including internal applications, databases, and electronic lab notebook systems such as Benchling. Your work will play a crucial role in ensuring the integrity, accuracy, and availability of our scientific metadata and analyses to all facets of the Altos organization.

Responsibilities

• Design and develop scalable data pipelines for transforming and migrating data from diverse, multi-modal sources to target systems, ensuring data quality, accuracy, and consistency throughout the process
• Collaborate with cross-functional teams, including software engineers, data engineers, data modelers, and research scientists to understand scientific data requirements and define schemas, transformation, storage, and migration strategies
• Perform data profiling and analysis to identify data quality issues, anomalies, and inconsistencies, and implement remediation strategies
• Develop and maintain data transformation and migration workflows, adhering to best practices and industry standards
• Monitor and troubleshoot data pipelines, proactively identifying and resolving performance bottlenecks, data integration issues, and data quality problems
• Stay up-to-date with emerging technologies, tools, and trends in data engineering.
• Document data transformation and migration processes, including data mappings, transformations, and dependencies, and maintain comprehensive documentation for future reference

Who You Are

Required Qualifications

• B.S. or M.S. degree in Computer Science, or related quantitative field, or equivalent technical experience.
• 2-5 years experience as a Data Engineer in a hands-on capacity, preferably in a biotechnology-focused or other life sciences research setting
• Strong programming skills in languages such as Python, Scala, Java, or JavaScript, and proficiency in SQL
• Strong understanding of relational and non-relational databases, data modeling principles, and query optimization techniques
• Familiarity with data integration tools and orchestration frameworks, such as Apache Airflow, Apache Spark, and/or Palantir Foundry
• Familiarity with cloud platforms, such as AWS, Azure, or Google Cloud, and their data services (e.g., AWS Glue)
• Experience designing and integrating data extraction processes using REST-like APIs
• Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment
• Excited to design, implement, and evangelize technical and cultural standards across scientific and technical functions

Preferred Skills

• Experience with scientific data management and documentation tools, including electronic lab notebook (ELN) systems (Benchling) and/or laboratory information management systems (LIMS)
• Experience with infrastructure as code (IaC) principles and technologies, such as Terraform or CDK
• Familiarity working with semantic data frameworks, including ontology management systems and knowledge graphs
• Knowledge of data governance, data security, and data privacy practices

The salary ranges for these position are

Redwood City: Data Engineer I is $124,950 to $169,050; Data Engineer II is 138,550 to 187,450

San Diego: Data Engineer I is $113,900 to $154,100; Data Engineer II is $128,350 to $173,650

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