Data Engineer/Senior Data Engineer

JOB DESCRIPTION

The Data Engineer/Senior Data Engineer will report to the Head of Data Science and work closely with team members across the organization to improve and maintain Volastra's data infrastructure, empowering researchers with data-driven insights.  This position requires hands-on experience designing and implementing data pipelines, warehousing solutions, analytics frameworks and data dashboards. The Data Engineer will be instrumental in accelerating our scientific discoveries by enabling researchers to effectively analyze complex multimodal datasets, identify promising therapeutic targets, optimize patient selection strategies, and prioritize research initiatives.

The ideal candidate combines technical expertise with strong problem-solving abilities, can work independently while supporting cross-functional initiatives, and has experience scaling data systems in a high-growth environment. They will establish and maintain best practices for our data architecture and infrastructure, making sure that all systems of ingesting data are efficient, scalable and maintainable.

Volastra is a fast-paced and growing biotech company with a culture of continuous learning and innovation. There are numerous opportunities for professional growth as we expand our data capabilities and tackle new challenges. The job is based in NYC with a flexible option for partial hybrid work.

RESPONSIBILITIES

• Design, build, and maintain scalable data pipelines and ETL processes to handle complex biological data, including high-throughput imaging and next-gen ‘omics datasets.  
• Design, build, and maintain analysis dashboards to empower researchers to gain more insights from their data.
• Develop and implement data warehouse architecture, ensuring optimal performance, reliability, and data quality for both structured and unstructured data 
• Collaborate with computational biologists, data scientists, wet lab researchers and leadership to understand data requirements and deliver solutions that accelerate rigorous, data-driven decision making.
• Create and maintain documentation for data systems, processes, and models while establishing best practices for data engineering.
• Optimize data infrastructure for performance, cost, and reliability while maintaining data security and compliance standards.
• Clearly communicate key findings to members of the scientific and leadership teams.
• Educate researchers on data management best practices and standards.
• Contribute to building a culture that embraces technical excellence, integrity, and collaboration internally and externally.

QUALIFICATIONS

• B.S. in Computer Science or a related discipline.
• 5+ years of experience in data engineering or similar technical roles.
• Strong programming skills in Python, R, SQL, and bash scripting and experience with modern data engineering tools.
• 3+ years of experience with cloud computing, preferably Databricks and AWS (e.g., Data Warehouse, Lakehouse, Unity Catalog, EC2, S3), with expertise in designing, developing, and maintaining data warehouses and lakes.
• Experience identifying data bottlenecks and implementing scalable ETL/ELT pipelines, with a proven track record of architecting effective solutions.
• Experience in designing and implementing software solutions, including coding and development, from initial concept to deployment, tailored for seamless use by non-technical end users (i.e. DevOps).
• Experience working with images and ‘omics data types (e.g. whole genome sequencing, RNA-seq, proteomics).
• Demonstrated expertise in designing and developing user-friendly cloud-based data analysis tools and dashboards (e.g., Shiny apps, Dash/Streamlit).
• Strong problem-solving skills with ability to work independently while collaborating effectively.
• Excellent communication skills with ability to effectively explain technical concepts to non-technical stakeholders.

PREFERRED SKILLS

• Experience with the Benchling electronic lab notebook system, including API and lab automation functionality.
• Experience and familiarity with machine learning models lifecycle, their maintenance and deployments (MLOps).
• Expertise in cloud resource management, with a focus on implementing best practices for data accessibility and robust security measures, including IAM role management and cloud policy enforcement.
• Experience working with bioinformatics tools and pipelines, particularly for processing NGS (e.g. Nextflow pipelines)

SALARY RANGE

Base salary of approximately $150,000- $175,000 which may vary depending on qualifications, experience, and ultimate leveling.