Top Python Jobs in Dublin

Lead Platform Engineer responsible for designing, building, automating, and operating enterprise PostgreSQL and Cassandra platforms. Ensure availability, performance, scalability, security, disaster recovery, and cloud migration. Lead automation (IaC, CI/CD), observability, capacity planning, and cross-team technical guidance for database modernization.

Lead Platform Engineer responsible for designing, building, automating, and operating enterprise PostgreSQL and Cassandra platforms. Ensure high availability, performance, security, DR, and scalability; drive cloud adoption and modernization; develop IaC, CI/CD, observability, and automated remediation; provide technical leadership and collaborate with infra, dev, and security teams.

Lead Platform Engineer responsible for design, build, automation, and operational support of enterprise PostgreSQL and Cassandra platforms. Duties include administration, performance tuning, HA/DR, cloud migrations, automation (IaC/CI-CD), observability, and cross-team technical leadership to ensure scalability, reliability, security, and compliance.

Lead Platform Engineer responsible for design, build, automation, and operational support of enterprise PostgreSQL and Cassandra platforms. Ensure high availability, performance, scalability, security, and compliance. Lead migrations, cloud adoption, IaC/CI-CD automation, observability, and provide technical leadership across database and infrastructure teams.

Lead design, build, automate, and operate mission-critical PostgreSQL and Cassandra database platforms. Ensure high availability, performance tuning, backup/recovery, security, cloud migrations, observability, and platform modernization while providing technical leadership and automation for enterprise environments.

Lead Platform Engineer responsible for design, build, automation, and operational support of enterprise PostgreSQL and Cassandra platforms. Duties include administration, upgrades, backup/recovery, performance tuning, HA/DR, capacity planning, cloud migration support, observability, and automation using IaC and scripting. Provides technical leadership, standards, and cross-team collaboration to ensure resilient, secure, and scalable database services.

Lead design and implementation of advanced analytics, reporting, and data tooling for chart review, targeting analytics, and risk adjustment. Build and validate data pipelines, automate integrations, ensure data quality, modernize legacy analytics, and deliver actionable insights to stakeholders across the organization.

Deliver targeted technical training and foundational webinars to large customers, update and scale enablement content, partner with Sales and Customer Success, mentor new hires, collaborate with Product and Engineering for product feedback, run internal and in-person enablement events, contribute to team OKRs, and stay current on observability and DevOps practices while delivering high CSAT.

Develop and maintain complex data pipelines and data sources using Snowflake, Airflow, Azure, SQL, and Python. Integrate on-premises and cloud data, build transformation routines, data models, stored procedures, masking solutions, monitoring tools, and automated data quality controls. Create CI/CD pipelines with GitHub Actions and collaborate with architects, analysts, and data stewards to deliver reliable analytics foundations. The role also supports scalable payment integrity data solutions and requires knowledge of data warehousing, integration, and security practices.

Develop and ship production machine learning and statistical algorithms for MongoDB’s core server, query engine, and Atlas platform. The role focuses on resource scaling, release safety, monitoring, automated incident response, and query performance. Responsibilities include prototyping, testing, deployment, model feedback loops, metrics and dashboards, code reviews, and collaboration with engineering teams to deliver measurable business impact.

Lead architecture and development of backend services, integrations, internal tools, and data systems for engineering metrics, tooling spend, ROI, and cost reporting. Build reliable APIs and auditable analytics products, replace manual processes, own testing, monitoring, and production support, and mentor engineers. Collaborate with product and business stakeholders while applying agentic engineering practices.

Build and maintain AI-driven support tooling and integrations: custom Zendesk apps, configure LLM-powered chatbots (Assembled), design conversation flows and fail-safes, connect support systems (Slack, Jira) via APIs or low-code platforms, and own production-ready automations and monitoring for Customer Operations.

The Security Automation Engineer designs and implements automation frameworks for security operations, focusing on compliance and scalable security controls for Managed Services platforms.

Provide deep technical support to customers and partners for MongoDB deployments: troubleshoot architecture, performance, recovery, and security; advise on best practices; collaborate with product and engineering teams; contribute to tooling and diagnostics; mentor new engineers and work closely with ISV partners to ensure joint customer success.

Provide advanced technical support to large MongoDB customers, resolving architecture, performance, recovery, security, database, cloud, and infrastructure issues. Advise customers on best practices for operating MongoDB at scale, collaborate with product and development teams, and build internal support tools for diagnostics, benchmarking, and performance analysis. The role requires strong troubleshooting, communication, customer service, teamwork, and the ability to learn quickly.

Build and operate foundational, security-critical platforms and cloud-native systems at scale. Automate infrastructure, reduce operational toil, define SLIs and SLOs, improve observability and incident response, perform capacity and performance analysis, and develop preventative reliability solutions. Participate in on-call rotations, post-incident reviews, technical design, and mentoring while collaborating with product, platform, and security engineering teams.

Leads enterprise product security across Google Cloud, AWS, AI applications, and software development. Designs security solutions, develops threat-modeling frameworks, conducts code reviews and vulnerability testing, integrates secure practices into the SDLC, and creates security policies. Triages threats, assesses risks, manages corrective actions, communicates findings to technical and executive stakeholders, and validates AI-assisted security recommendations for security, resiliency, data protection, and auditability.

The role involves applying advanced analytics in healthcare, developing coding solutions, collaborating with teams, and mentoring. Focus is on data science and improving healthcare outcomes.

Design, implement, and support features for the MongoDB Atlas API Platform and developer tools (e.g., Atlas CLI). Build IaC tooling and integrations, work with cloud platforms, ship incremental features, investigate customer issues (Level 2 support rotation), and collaborate across distributed teams while mentoring peers.

Explore and validate complex enterprise datasets, conduct exploratory analyses and experiments, build reusable Databricks SQL and Python notebooks, identify data quality issues, and translate ambiguous business questions into evidence-based product recommendations. The role partners with stakeholders, documents analytical findings, creates semantic-layer assets, and supports transition of validated concepts to downstream engineering teams.

Build tooling, services, and reusable patterns to apply generative and agentic AI across products. Design, implement, and evaluate AI-enabled apps and developer workflows; improve developer experience via automation and platform capabilities; partner with stakeholders to deliver prototypes to production and share best practices across Mastercard.

Build and ship AI-enabled applications, tooling, and platform capabilities for agentic AI. Design reusable services, evaluate models and frameworks, improve developer workflows, and partner across product and engineering to prototype and scale AI solutions.

Design, build, and scale agentic and generative AI tooling, services, and developer-facing platforms. Implement AI-enabled applications, evaluate models and frameworks, improve developer experience, and partner with product and business stakeholders to prototype and productionize solutions.

Build tooling, services, and reusable patterns to apply Generative and Agentic AI to products and developer workflows. Design and implement AI-enabled applications and integrations, evaluate models, develop prototypes from concept to validation, and improve developer experience through automation and platform capabilities while partnering with product and business stakeholders.

Design and build Agentic AI tooling, services, and reusable patterns. Implement AI-enabled applications and developer-facing capabilities, evaluate models and frameworks, develop frontend (React/Next.js) and backend (Java/Python) systems, improve developer experience via automation and CI/CD, and partner with stakeholders from prototype to validation while sharing best practices.