Role Overview OrbitNexa is looking for an experienced Data Scientist / Bioinformatics Engineer with proven hands-on experience in building human genome bioinformatics pipelines and a track record of successfully delivering bioinformatics projects. This is an excellent chance for someone who is passionate about developing and optimizing human genome analysis pipelines using AWS HealthOmics and other AWS services. You'll work on cutting-edge human genomics and bioinformatics projects, collaborate with healthcare and research teams, and contribute to building scalable, efficient bioinformatics solutions for human genome analysis.

You'll have the opportunity to work with AWS HealthOmics, Nextflow, WDL, and modern cloud-based bioinformatics tools to process and analyze large-scale human genomic data. We are seeking candidates who have demonstrated ability to deliver end-to-end human genome bioinformatics solutions from design to production deployment. Candidates with strong human genome pipeline experience will be considered even if they have limited or no direct AWS HealthOmics experience, as we value hands-on bioinformatics expertise.

In This

Role, You Will Develop and optimize human genome bioinformatics pipelines using AWS HealthOmics (Omics Workflows)

Design and implement scalable human genomic data processing workflows on AWS

Build and maintain Nextflow and WDL (Workflow Description Language) pipeline definitions for human genome analysis

Integrate human genome bioinformatics tools and algorithms into cloud-native workflows

Process and analyze large-scale human genomic datasets (WGS, WES, RNA-seq, etc.)

Build pipelines for human genome variant calling, annotation, and interpretation

Optimize pipeline performance, cost, and resource utilization on AWS

Implement data quality control, validation,



and error handling in pipelines

Work with AWS HealthOmics Sequence Stores, Annotation Stores, and Reference Stores

Design and implement data processing workflows using AWS Batch, Step Functions, and Lambda

Build data transformation and ETL pipelines for genomic data

Implement data storage and retrieval strategies using S3, DynamoDB, and HealthOmics stores

Develop monitoring, logging, and alerting solutions using CloudWatch

Create data visualization dashboards and reports for bioinformatics results

Collaborate with research scientists and clinicians to understand requirements

Document pipeline architecture, workflows, and best practices

Implement version control and reproducibility for bioinformatics pipelines

Optimize costs and resource allocation for large-scale genomic processing

Integrate with laboratory information systems (LIS/LIMS) and healthcare systems

Ensure compliance with healthcare data regulations (HIPAA, GDPR) in data processing

Deliver end-to-end bioinformatics projects from requirements gathering to production deployment

Participate in code reviews, sprint planning, and team discussions

Stay updated with latest bioinformatics tools, AWS HealthOmics features, and genomics research To Be Successful You Will Bachelor's or Master's degree in Bioinformatics, Computational Biology, Data Science, Computer Science, or related field (PhD preferred)





3-5 years of professional hands-on experience in bioinformatics with proven track record of successfully delivering human genome bioinformatics projects from conception to production

2+ years of hands-on experience building and optimizing human genome bioinformatics pipelines with demonstrated project outcomes and strong portfolio demonstrating completed projects with measurable results

Deep expertise in human genome bioinformatics: variant calling (germline & somatic), annotation, interpretation, and analysis using tools like GATK, DeepVariant, Strelka2, Mutect2, VEP, ANNOVAR, BWA, and following GATK best practices

Strong proficiency in Python and/or R for bioinformatics analysis, with experience in Nextflow and/or WDL for pipeline development

Deep understanding of human genomic data formats (FASTQ, BAM, CRAM, VCF, gVCF) and reference assemblies (GRCh37, GRCh38) with knowledge of annotation databases (dbSNP, ClinVar, gnomAD)

Experience with AWS HealthOmics or similar cloud genomics platforms (preferred, but candidates with strong human genome pipeline experience will be considered even without direct HealthOmics experience)

Understanding of AWS services (Batch, Step Functions, Lambda, S3, DynamoDB, CloudWatch) or similar cloud platforms, with experience in containerization (Docker) and high-performance computing for genomics

Experience with version control (Git), data quality control, validation, QC metrics, and statistical analysis for genomic data

Valid cloud certification in AWS, Azure, or GCP (preferred)

Strong problem-solving, analytical thinking, and excellent communication skills with ability to work independently and in a team

Experience with healthcare/healthtech domain, HIPAA-compliant systems, clinical genomics, or precision medicine (preferred)

📌 Data Scientist / Bioinformatics Engineer (Hyderabad)
🏢 Orbitnexa Technologies
📍 Hyderabad