Sr Bioinformatics Software Engineer

Baylor Genetics•Houston, TX

About The Position

The Senior Bioinformatics (BI) Software Engineer holds a critical technical role, responsible for designing, developing, and maintaining scalable and efficient software solutions for Baylor Genetics’ bioinformatic pipelines. This role involves collaborating with and supporting cross-functional teams to deliver data-driven software solutions aligning with business needs.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Bioinformatics or a related field; Master’s degree preferred.
Minimum of 5 years of experience in software development, with a proven track record of designing and implementing scalable software solutions based on diverse user feature needs.
Must have a proven track record of implementing production ready software solutions from scratch.
Deep knowledge and expertise in at least two programming languages (Python, Perl, R, or Bash, will also consider Java, C++, and Groovy).
Proficient in a range of database technologies, including SQL Server, NoSQL, MongoDB, MySQL, and ElasticSearch, demonstrating comprehensive skills in database management, optimization, and query development.
Proficiency in working in an Agile framework and implementing CI/CD practices using Git.
Implementation of object orientated programming (OOP) is second nature, which includes building intuitive classes relevant to the science, system, or service.
Standard software design practices relevant to that language is intuitive to you.
Demonstrated ability to build entire software packages from scratch that are performant and highly maintainable, ensuring they are tested and are production ready.
Solid understanding and habitual practice of unit and integration testing of software.
High regard for documentation and object/variable naming that is explicit, with the ability to relay or distill scientific concepts within supplemental documentation or inline code itself.
Proficiency in designing and building APIs and microservices from scratch.
Solid understanding of package management practices (PIP, Conda, etc.) and containerization (Docker, Singularity, etc.).
Strong analytical and problem-solving skills with the ability to translate complex business needs into technical solutions and work independently to solve problems.
Also requires good communication skills and flexibility to reach out to stakeholders and SMEs as necessary.
Excellent interpersonal and communication skills to collaborate effectively with multidisciplinary teams.
Should be open and willing to receive and give criticism and feedback in a measured manner, focused on solving the problem at hand.
Ability to adapt to evolving technologies, learn new tools, and implement best practices in BI software engineering and development.
Should be able to assess situations when a drop-in solution would be preferable to a custom software implementation and run proof-of-concepts as needed.
Should be highly familiar with best practices in software development and an advocate of best practices, even under pressure.
Experience in managing individual projects and adhering to timelines while delivering high-quality solutions, ensuring good communication in situations where project scopes may fluctuate.

Nice To Haves

Prior experience or domain knowledge from collaborating with laboratory scientists, computational biologists, or clinical reviewers is a nice-to-have.
Knowledge of Azure is a bonus.
Familiarity with Linux OS and HPC clusters (SLURM, Kubernetes, GCP, Azure, etc.) is a plus, but not essential.
Proficiency or knowledge of workflow management or orchestration tools (Nextflow, Airflow, Snakemake, etc.) is a plus, but not not essential.

Responsibilities

Design, develop, and maintain robust software solutions using various tools, databases, and technologies to meet business requirements.
Create and optimize data models, ensuring the accuracy, integrity, and performance of the underling computational algorithms, especially as pertains to assembly, mapping, variant calling and variant annotation.
Develop and optimize ETL (Extract, Transform, Load) processes to efficiently extract data from various sources, transform it, and load it into the BI system, with an emphasis on utilizing APIs.
Analyze and optimize SQL queries and database performance to enhance data retrieval and reporting speed. Contribute to schema design and review sessions to ensure high performance and maintainable databases.
Develop interactive dashboards and automated reports using BI tools (e.g., Azure Pipelines, Teams Power Automate, email, Nextflow) to provide actionable insights for stakeholders.
Work and align closely with stakeholders, including data analysts, business users, clinical reviewers, laboratory personnel and software developers, to scope their requirements and deliver timely integrations of new software.
Integrate disparate data sources and ensure consistency, accuracy, and reliability of data across the BI system, with a focus on devising systems that have minimal to no code debt and are highly maintainable and flexible.
Conduct rigorous testing of BI solutions to ensure data accuracy, system stability, and optimal performance, with the ability to automate testing suites using packages (e.g. pytest, doctest, Azure Pipelines).
Create comprehensive documentation for developed solutions and provide support and maintenance as necessary. This generally includes: (1) detailed in-line commenting noting Jira ticket request numbers, genomic diagrams, reasoning and personal thoughts, TODO comments, docstrings, BG headers, etc.; (2) wikis and README files instructing users on how to install and implement the software along with trace mappings detailing how the software is generally organized.
Performs other advanced job-related duties as assigned.