AstraZeneca

5 days ago

Senior Data Engineer — Lab Data Pipelines & Data Mesh (12 month FTC)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Build end-to-end lab data pipelines that connect instruments, robotics, and scientific systems into governed, AI-ready data products. You’ll design standardized ingestion and transformation, publish domain data products in a Databricks/Delta Lake mesh on AWS, and automate ELN-to-mesh extraction with clear provenance. Partner across scientists, automation/robotics, informatics, IT, and lab stakeholders while embedding quality, security, monitoring, and reliability into production workflows.

Location: Ireland

Workplace: Onsite

Employment Type: Contract · 12 months

Job Function: Laboratory & Clinical Operations

Seniority: Mid level

Key Responsibilities

•Engineer resilient lab-to-cloud connectivity across instruments, lab equipment, and robotics from diverse vendors and data types.
•Design and deliver automated ingestion, validation, transformation, and loading into standardized, analysis-ready datasets.
•Curate and publish domain data products in a lake-house-based data mesh (Databricks on AWS) for self-service analytics and ML.
•Implement ELN-to-mesh automation using agentic/LLM-assisted extraction into governed data products with clear provenance.
•Embed quality, security, compliance, and reliability through auditability, data integrity controls, and monitoring (logging, alerting, lineage, retries, runbooks).

Travel: Medium travel

Key Requirements

•BS in Computer Science, Data Engineering, Software Engineering, Bioinformatics, Statistics, Engineering, or related; MS a plus.
•5+ years in data/software engineering delivering production-grade pipelines (life sciences lab environment valued).
•Strong Python and SQL, including data pipeline orchestration patterns and data modeling for analytics/AI use cases.
•Hands-on AWS experience (IAM, S3, EC2/EKS/Glue, monitoring) and Databricks/Delta Lake.
•Experience integrating heterogeneous sources (files, vendor exports, REST APIs) and building resilient ingestion for real-world lab data.

Experience:5+ yearsLife sciencesBiotechLab dataData mesh

Education:Bachelor's

Skills:CollaborationCommunicationOwnership

Certifications:PMPPgMPCertified ScrumMaster (CSM)Agile Certified Practitioner (PMI-ACP)

Tech Stack:PythonSQLAWSIAMS3EC2EKSGlueDatabricksDelta LakeREST APIsELNLLMMachine learningAnalytics

Company Brief

AstraZeneca

Global biopharmaceutical company discovering, developing and commercializing prescription medicines across oncology, cardiovascular, renal & metabolism, respiratory, and immunology, focused on innovative therapies and vaccines to improve patient outcomes worldwide.

Industry: Pharmaceuticals

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cambridge, United Kingdom

Founded: 1999

Glassdoor: 3.8

Website LinkedIn

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AstraZeneca

5 days ago

Senior Data Engineer — Lab Data Pipelines & Data Mesh (12 month FTC)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: Ireland

Workplace: Onsite

Employment Type: Contract · 12 months

Job Function: Laboratory & Clinical Operations

Seniority: Mid level

Key Responsibilities

•Engineer resilient lab-to-cloud connectivity across instruments, lab equipment, and robotics from diverse vendors and data types.
•Design and deliver automated ingestion, validation, transformation, and loading into standardized, analysis-ready datasets.
•Curate and publish domain data products in a lake-house-based data mesh (Databricks on AWS) for self-service analytics and ML.
•Implement ELN-to-mesh automation using agentic/LLM-assisted extraction into governed data products with clear provenance.
•Embed quality, security, compliance, and reliability through auditability, data integrity controls, and monitoring (logging, alerting, lineage, retries, runbooks).

Travel: Medium travel

Key Requirements

•BS in Computer Science, Data Engineering, Software Engineering, Bioinformatics, Statistics, Engineering, or related; MS a plus.
•5+ years in data/software engineering delivering production-grade pipelines (life sciences lab environment valued).
•Strong Python and SQL, including data pipeline orchestration patterns and data modeling for analytics/AI use cases.
•Hands-on AWS experience (IAM, S3, EC2/EKS/Glue, monitoring) and Databricks/Delta Lake.
•Experience integrating heterogeneous sources (files, vendor exports, REST APIs) and building resilient ingestion for real-world lab data.

Experience:5+ yearsLife sciencesBiotechLab dataData mesh

Education:Bachelor's

Skills:CollaborationCommunicationOwnership

Certifications:PMPPgMPCertified ScrumMaster (CSM)Agile Certified Practitioner (PMI-ACP)

Tech Stack:PythonSQLAWSIAMS3EC2EKSGlueDatabricksDelta LakeREST APIsELNLLMMachine learningAnalytics

Company Brief

AstraZeneca

Industry: Pharmaceuticals

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cambridge, United Kingdom

Founded: 1999

Glassdoor: 3.8

Website LinkedIn