Adaptimmune

Senior IT DevOps Data Engineer

Information Technology - Abingdon, Oxfordshire, United Kingdom - Full Time

 

Primary Responsibility

Data engineering is the practice of making the appropriate data accessible and available to data scientists, business analytics teams and decision makers for the purposes of scientific analysis.   The senior IT DevOps Data Engineer will administrate production tools and environments and work on implementing new IT solutions.   This is a hands-on IT role that blends software development, DevOps and bioinformatics.   He/she will work closely with scientific and IT experts, business analytics teams, and decision makers to enable data access, integrated data reuse and vastly improve time-to-solution for data and analytics initiatives. 

The scope of this role includes:

  • Understanding of data and analytic requirements to choose the right IT tools, ways of working and solutions for the job (i.e. speed versus reuse; ad-hoc versus production)
  • Administrate and enhance production tools, applications, systems and underlying IT environment
  • Develop IT frameworks, architectures, integration ETL schemes, databases, production pipelines, visualization and applications for large-scale data processing from data source ingestion to end user consumption
  • Apply data governance and data security requirements to solutions

 

This role will require both creative and collaborative working with IT experts, scientists, and line function analytical bioinformaticians.  The senior IT DevOps Data Engineer will support fast paced ad-hoc data analysis, individual projects and longer-term enterprise-wide solutions.

 

Key Responsibilities

1   Understanding of data and analytic requirements to choose the right IT tools, ways of working and solutions for the job (i.e. speed versus reuse; ad-hoc versus production)

2   Administrate and enhance production tools, applications, systems and underlying IT environment

  • Engage with others as subject matter expert and IT system owner for technology stack
  • Install, operate and configure the entire technology stack (including containerized applications)
  • Deploy the technology stack to support line function bioinformatics and data analytics
  •  Partner with IT infrastructure group for storage, server and network needs

3   Hands-on develop IT frameworks, architectures, integration ETL schemes, databases, production pipelines, visualization and applications for large-scale data processing

  • Data source ingestion to end user visualization
  • Assemble large, complex data sets that meet functional and non-functional business requirements
  • IT requirements, design and test documents to support technical implementation
  • Set up and operate heavy lifting associated with engineering data for analytics
  • Move IT solutions effectively into production, and manage / optimize these solutions for end users
  • Automate manual processes for data preparation and integration, optimize data delivery, re-design infrastructure for greater scalability, etc. to improve productivity
  • Streamline and prepare data for analysis through understanding of data flow and integration
  • Create and drive standards for data capture, storage, and transformation

4   Apply data governance and data security requirements to solutions

  • Participate in ensuring compliance and governance during data use
  • It will be the responsibility of the data engineer to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives
  • Work with data governance teams (and information stewards within these teams) and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse

5   Other duties as assigned by management in support of rapidly growing company

 

Qualifications & Experience

Required

  • A bachelor or master degree in computer science, statistics, applied mathematics, computational biology, data management, data science, information systems, bioinformatics or a related field
  • Combination of IT software engineering, DevOps, package application programming, data engineering, data integration, and data visualization skills with data science or big data experience
  • Demonstrated extensive hands-on work experience in developing IT solutions and DevOps for big data
  • Strong collaboration and partnering skills – able to interact with IT and business experts easily
  • Deep understanding of computational methods, scripting and programming languages, and relevant concepts in cancer biology, immunology and/or genetics
  • Good understanding of in-process manufacture, research and clinical trial data
  • Ability to easily partner with business users and speak the language of data with the business
  • High energy, confident, gets things done, yet easy going personality

Desirable

  • Outstanding communication, collaboration and partnering skills
  • Prior experience implementing centralized integrated data and analytics tools and solutions
  • Experience in biotechnology field
  • Experience in Next Generation Sequencing-RNA sequencing data and other bioinformatics tools
  • High performance computing in Cloud
  • GxP experience
  • Immuno-oncology experience

 

Skills & Compentencies

Required

  • Strong automation skills (tool agnostic)
  • The ability to design, build, and operate a technology stack
  • Configuration and automation management, health checks, single point of failure, notifications
  • Expert skill in the following tools and coding languages: Docker, Portainer / GitLab, Github, Jenkins, JIRA, Complex SQL, PL/SQL, Bash, Python, R, Javascript, C++, PHP, HTML
  • Experience with following bioinformatic pipeline tools:   Galaxy, Partek Flow, OmnicSoft, Seqmonk, Rstudio, Jupyter
  • Experience with following monitoring tools:  Prometheus, Nagios, Splunk
  • Strong operational and administrative experience in Linux environment
  • Experience with AWS in a production environment: EC2, S3, VPC, IAM, ELB, CloudWatch, Apps, Consoles
  • Basic experience working with popular data discovery, analytics and BI software tools like Spotfire, Tableau, Qlik, PowerBI, etc. for semantic-layer-based data discovery and end user visualization
  • Effective cross-functional partnering skills
  • Ensuring operational best practices by working closely with the deployment/releasing teams
  • Demonstrated ability to design, build and manage “production ready” data pipelines for data structures encompassing data transformation, data integration, data models, schemas and meta-data
  • Experience with integration of data from multiple data sources to support down-stream scientific analysis
  • Experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms
  • Basic experience in working with data governance/data quality and data security teams in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
  • Demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems
  • Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization

Desirable

  • Prior experience as bioinformatician, biotech software programmer or data architect a plus
  • Highly collaborative and supportive of business and of its ideals and strategies
  • Practical in approach to decision making, recommendations and problem solving that is principle-based
  • An understanding of the principles of oncology / immuno-oncology
  • Prior experience in complex biotechnology and / or pharmaceuticals industry
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