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Bioinformatics Data Engineer Jobs in Boston, MA (NOW HIRING)

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IT Data Engineer - BB4352 BB4352 Cambridge, MA 12+ Months Job Summary: We are seeking a highly ... automated bioinformatics/data science pipelines that enable researchers and scientists to ...

Required : • Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline; PhD preferred. • Minimum 10 years of hands-on experience ...

Experience with programming and data analysis in languages such as R and/or Python, and familiarity ... bioinformatics, AI, or data science. How we do it At AstraZeneca,we'rededicated to being a Great ...

Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline; PhD preferred. * Minimum 10 years of hands-on experience architecting and ...

We are seeking a motivated and curious Scientific Data Engineer at the beginning of their ... Degree in bioinformatics, computational biology, data science, computer science, or a related field ...

Watershed enables scientists to conduct all essential analysis - from lab data to plot - with a single software platform. We have attracted some of the best bioinformatics, engineering, and ...

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Bioinformatics Data Engineer information

See Boston, MA salary details

$46.7K

$142.4K

$259.1K

How much do bioinformatics data engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for bioinformatics data engineer in Boston, MA is $142,376.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,300.00 and $170,600.00 per year, depending on experience, location, and employer.

What is a bioinformatics data engineer?

A Bioinformatics Data Engineer is a professional who designs, develops, and maintains data infrastructure for managing and analyzing large-scale biological data, such as genomics or proteomics datasets. They build pipelines and tools to process, store, and retrieve complex biological information efficiently. Their work enables researchers and scientists to access and interpret data for discoveries in fields like medicine, genetics, and biotechnology. Often, they collaborate closely with bioinformaticians, data scientists, and software engineers to support research initiatives.

How do bioinformatics data engineers typically collaborate with researchers and other teams in a biomedical organization?

Bioinformatics Data Engineers often work closely with biologists, data scientists, and software engineers to ensure the effective collection, processing, and analysis of complex biological data. They regularly participate in cross-functional meetings to understand research goals, develop data pipelines, and troubleshoot data-related issues. Collaboration is essential, as engineers must translate scientific requirements into technical solutions, provide data access and visualization tools, and support researchers in extracting meaningful insights from large datasets. This teamwork fosters a dynamic environment where communication and adaptability are key.

What are the key skills and qualifications needed to thrive as a bioinformatics data engineer, and why are they important?

To thrive as a Bioinformatics Data Engineer, you need a strong background in computer science, biology, and statistics, often supported by a relevant degree and experience in data engineering. Proficiency with programming languages (such as Python, R, or SQL), bioinformatics tools, cloud platforms, and big data frameworks (like Hadoop or Spark) is typically required. Strong problem-solving, collaboration, and communication skills help you work effectively across interdisciplinary teams and convey complex findings. These skills ensure accurate analysis, efficient data pipeline development, and meaningful insights that advance biological research and healthcare solutions.

What is the difference between Bioinformatics Data Engineer vs Bioinformatics Analyst?

AspectBioinformatics Data EngineerBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; programming skillsBachelor's or Master's in Bioinformatics, Biology, or related fields; data analysis skills
Work EnvironmentData pipelines, database management, software developmentData interpretation, report generation, biological data analysis
Employer & Industry UsageBiotech companies, research labs, pharmaResearch institutions, healthcare, biotech
Common Search & ComparisonFocuses on data infrastructure and pipelinesFocuses on biological data interpretation

The main difference between a Bioinformatics Data Engineer and a Bioinformatics Analyst lies in their focus areas. Data Engineers build and maintain data pipelines and infrastructure, while Analysts interpret biological data to generate insights. Both roles require strong bioinformatics knowledge, but Data Engineers emphasize programming and data management, whereas Analysts focus on biological interpretation and reporting.

What are popular job titles related to Bioinformatics Data Engineer jobs in Boston, MA?

For Bioinformatics Data Engineer jobs in Boston, MA, the most frequently searched job titles are:

What cities near Boston, MA are hiring for Bioinformatics Data Engineer jobs?

Cities near Boston, MA with the most Bioinformatics Data Engineer job openings:

Infographic showing various Bioinformatics Data Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $142,376 per year, or $68.5 per hour.

IT Data Engineer - BB4352

TechData Service Company LLC

Cambridge, MA • On-site

$70 - $95/hr

Temporary

Medical, Dental, Vision

Posted 17 days ago

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Job description

IT Data Engineer – BB4352

 

 

BB4352

Cambridge, MA

12+ Months

Job Summary:

We are seeking a highly skilled IT Data Engineer with expertise in DatabricksSeqera Platform (Nextflow Tower), cloud data engineering, and scientific data workflows to support our Discovery R&D and data science initiatives. The ideal candidate will design, develop, and maintain scalable data platforms and automated bioinformatics/data science pipelines that enable researchers and scientists to efficiently process, analyze, and access large-scale scientific and business datasets.

This role requires strong experience in cloud-native architectures, data engineering best practices, workflow orchestration, and collaboration with cross-functional teams including scientists, bioinformaticians, data scientists, and IT infrastructure teams.

Key Responsibilities:

·         Data Engineering & Platform Development

·         Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and cloud-native technologies.

·         Build and optimize ETL/ELT processes for structured, semi-structured, and unstructured data.

·         Develop data ingestion frameworks for research, laboratory, clinical, and external scientific datasets.

·         Implement data quality, validation, monitoring, and governance processes.

·         Support enterprise data lakehouse architecture and data platform modernization initiatives.

·         Databricks Administration & Development

·         Develop and maintain Databricks notebooks, workflows, Delta Live Tables, and Jobs.

·         Create optimized Spark-based transformations and data processing solutions.

·         Implement Medallion Architecture (Bronze, Silver, Gold) for data lifecycle management.

·         Manage Delta Lake environments and optimize performance, scalability, and cost.

·         Integrate Databricks with cloud-native services and enterprise applications.

·         Seqera Platform & Scientific Workflow Management

·         Deploy, configure, and support Seqera Platform (formerly Nextflow Tower).

·         Develop and maintain Nextflow pipelines for bioinformatics, genomics, imaging, AI/ML, and scientific computing workloads.

·         Integrate Seqera workflows with AWS cloud infrastructure and compute environments.

·         Support containerized workflows using Docker and Kubernetes technologies.

·         Enable reproducible, scalable, and compliant scientific data processing workflows.

·         Cloud Engineering

·         Design and implement cloud-based data solutions in AWS.

·         Manage cloud storage solutions including S3 and data lifecycle policies.

·         Develop Infrastructure-as-Code solutions using Terraform or CloudFormation.

·         Implement security controls and access management following enterprise IT standards.

·         Partner with data scientists, researchers, bioinformaticians, and business stakeholders to understand data requirements.

·         Provide technical guidance on data engineering best practices and workflow automation.

·         Troubleshoot pipeline failures, performance issues, and workflow bottlenecks.

·         Contribute to platform roadmaps and continuous improvement initiatives.

·         Maintain technical documentation, SOPs, and knowledge articles.

Required Qualifications

·         Education

o    Bachelor's degree in Computer Science, Information Technology, Data Engineering, Bioinformatics, or a related technical field.

o    Master's degree preferred.

o    Experience

o    5+ years of experience in data engineering, cloud engineering, or analytics platform development.

o    3+ years of hands-on experience with Databricks and Apache Spark.

o    2+ years of experience with Seqera Platform (Nextflow Tower) and Nextflow workflows.

o    Experience supporting scientific research, life sciences, pharmaceutical, biotech, or healthcare environments preferred.

·         Technical Skills

o    Databricks & Data Engineering, Databricks Lakehouse Platform

o    Apache Spark (PySpark, Spark SQL)

o    Delta Lake, Delta Live Tables (DLT)

o    Databricks Workflows

o    Unity Catalog

o    SQL and Python

o    Seqera & Scientific Computing; Seqera Platform / Nextflow Tower

o    Nextflow pipeline development

o    Bioinformatics workflow automation

o    Docker and container technologies

o    Kubernetes orchestration

o    High-performance computing environments

o    Cloud Technologies, AWS (required)

o    S3, IAM, EC2, VPC, Lambda

o    Terraform or CloudFormation

o    Cloud monitoring and logging tools

o    Data Technologies

o    Data Lake and Lakehouse architectures

o    ETL/ELT frameworks

o    Data modeling

o    Data cataloging and governance

o    API integrations

o    Data quality frameworks

o    DevOps & Automation

o    GitHub/GitLab

o    CI/CD pipelines

o    Jenkins, GitHub Actions, or similar tools

o    Infrastructure as Code

o    Agile and DevOps methodologies

Core Competencies

·         Strong analytical and problem-solving skills.

·         Excellent communication and stakeholder management abilities.

·         Ability to work independently and within global cross-functional teams.

·         Strong attention to detail and commitment to data quality.

·         Continuous improvement mindset and passion for innovation.

TechData is now a part of Quantive Intelligence, same people, expanded capabilities and we are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Company Description

https://quantive.bio/