Bioinformatics Data Engineer ( Python / Shell Scripting / Docker )

• (Important Notes: (1) It is a Desk Job (Onsite Job), operating for 6 days / week working pattern
• 5 days working from an office environment and Saturday currently allowed with remote working and (2) Immediate Joiners Preferred)

Job Summary

• We are looking for a highly skilled Data Engineer with strong programming and workflow automation skills to support and enhance our production bioinformatics pipelines.
• You do not need a biology background
• but you must be comfortable working with biological data formats, large datasets, and cloud-based workflows.
• In this role, you will develop, maintain, and optimize our data processing pipelines used for NGS (Next-Generation Sequencing) analysis, clinical workflows, and research innovation.
• You will work closely with bioinformaticians, software engineers, and data scientists to build scalable, reliable, and efficient systems.

Responsibilities

• Pipeline & Data Engineering:
• Develop and maintain scalable data pipelines for genomic and clinical datasets.
• Build workflow automation using Python, Shell, Docker, and workflow managers (Nextflow, Snakemake, Airflow, etc.).
• Optimize existing pipelines for performance, resource usage, and reliability.
• Handle large biological datasets (FASTQ, BAM, VCF, CSV/TSV, metadata).
• Software Engineering:
• Write clean, modular, production-level code in Python and Shell.
• Implement CI/CD processes for pipeline deployment.
• Maintain code repositories (Git) and ensure high-quality documentation.
• Cloud & Infrastructure:
• Work with AWS/GCP/Azure services for scalable pipeline execution.
• Manage container-based deployments using Docker.
• Monitor job performance, logs, and system behavior.
• Data Management:
• Maintain data integrity, versioning, and audit trails.
• Develop automated QC checks and validation workflows.
• Support data ingestion, transformation, and ETL processes.
• Collaboration:
• Work with bioinformaticians to translate analysis logic into scalable workflows.
• Collaborate with clinical and operations teams to ensure pipeline readiness.
• Troubleshoot pipeline failures and optimize workflows in production.

Required Skills: Core Technical Skills

• Strong proficiency in Python
• Hands-on experience with Shell scripting (bash)
• Strong understanding of Docker / containerization
• Knowledge of Git, CI/CD, and software development best practices
• Experience with workflow orchestration: Nextflow, Snakemake, Airflow, Cromwell, Prefect (any one) Data Engineering Skills:
• Experience with large datasets, ETL pipelines, log processing
• Strong understanding of file formats, data transformation, and automation
• Familiarity with Linux and HPC or distributed systems Bioinformatics Data Handling (Training can be provided):
• Understanding of at least one biological data type: FASTQ, BAM/CRAM, VCF, BED, GTF
• Ability to process unstructured or semi-structured scientific data Good to Have Skills (Will Prefer If Available):
• Experience with R
• Exposure to ML/AI workflows
• Experience with cloud (AWS Batch, Lambda, S3, EC2)
• Knowledge of Next Generation Sequencing (NGS) pipelines
• Familiarity with database systems (SQL/NoSQL)