Data Infrastructure Engineer/Senior Data Infrastructure Engineer

Found in: beBee jobs US - 7 days ago


South San Francisco, California, United States Calico Full time

Who we are:

Calico is a research and development company whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan, and to devise interventions that enable people to lead longer and healthier lives. Executing on this mission will require an unprecedented level of interdisciplinary effort and a long-term focus for which funding is already in place.

Position Description:

Calico is seeking an exceptional Data Engineer to join our software and computing group. Great software engineering is increasingly crucial to biology. We are in the midst of an explosion of biological and medical data that will transform our understanding of biology and disease, but the tools to store, process, visualize, explore, and analyze these data are often primitive—and in some cases don't yet exist. Come be a part of changing that story.

In this role, you will work closely with computational and research scientists to define strategies and implement robust systems for modeling, collecting, storing, and accessing diverse scientific data and metadata. Collaborating with other scientists and engineers, you will design, build, and maintain databases and data warehouses that underpin our scientific endeavors and accelerate our ability to ask new, sophisticated questions spanning multiple organisms, data modalities, and timescales. You will not only build tools to support existing scientific workflows, but also help set the vision for future data generation and collection efforts.

If you are passionate about data, passionate about biology, and passionate about their intersection—this is the job for you.

What you'll do:

Work with computational and research scientists to understand, architect, and build solutions to address common analysis use cases and improve data accessibility
Design strategies for data ingestion, storage, transformation, and integration across heterogeneous internal and external data sources
Implement, document, and maintain processing pipelines, databases, and data warehouse + data lake infrastructure
Develop APIs and GUIs for accessing and visualizing scientific data
Set data engineering vision and drive both independent and collaborative software development projects end-to-end
Contribute to a range of projects, from one-off solutions to long-term, complex systems
Build out core infrastructure, tooling, and software development processes

Position requirements:

5+ years building Python-based backend systems
3+ years working with contemporary workflow / ETL tools and frameworks (e.g., Airflow, Luigi, etc.)
Fluent knowledge of RDBMS (PostgreSQL, MySQL)
Experience implementing RESTful APIs, GraphQL, and other programmatic interfaces to complex multidimensional data
Firm grasp of software design best practices (test-driven development, API design, etc)
Demonstrated success in owning projects end-to-end, including working with non-technical stakeholders to define requirements and seek feedback

Nice to haves:

Worked in biology or life sciences and have familiarity with databases and data types used by computational biologists
Experience with cloud data warehouse solutions e.g. Snowflake, BigQuery, Redshift
Strong understanding of the Python data ecosystem (NumPy, pandas, Jupyter, etc.)
Worked with machine learning tools and infrastructure, e.g. TensorFlow and PyTorch
Experience working with diverse and cutting-edge high-dimensional datasets (e.g., RNASeq, metabolomics, high-content imaging)
Built backends for high-dimensional graph or network data
Experience deploying flexible + high-performance data backends and interfaces in the cloud with Google Cloud Platform, Amazon Web Services, or similar platforms
Designed or worked with auditable data systems suitable for regulatory review
Experience with on-prem high-performance computing clusters (e.g. SLURM)

Some projects you may contribute to:

Data warehouse—a system to extract, transform, and load public and private datasets into a single repository, then making these data available for analysis visually with either off-the-shelf or custom-built GUIs
Data lake—a system to leverage the wide variety and depth of Calico's datasets to enable interoperability, repeatability, and to serve as a foundation for cross-functional analytic tools
Exploratory data visualization & analysis tools—apps to help scientists explore and understand diverse, complex, and multidimensional data
Full-stack experience with our Data Platform and Data lake projects that our scientists use to manage and process experimental data
Automation—software to ingest and transform data from custom high-throughput instrumentation

Calico focuses on Biotechnology, Machine Learning, Bioinformatics, Drug Discovery, and Science. Their company has offices in South San Francisco. They have a large team that's between employees.
You can view their website at or find them on LinkedIn.
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