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Software EngineeringJob Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Location: Dublin
Job Summary:
Salesforce’s Employee Success (ES) Product Management team is advancing AI-driven data initiatives to expand our data capabilities across all ES functions. A key priority is developing a robust data and AI foundation to support innovation, automation, and data-driven decision-making.
We are seeking a highly skilled Lead Data Engineer with expertise in data engineering, AI, and machine learning, along with experience in API development. Familiarity with Salesforce Data Cloud and Agentforce is a plus.
In this role, you will build data pipelines, metrics, analytics solutions, and Agentic AI solutions used by employees globally. You will partner with business teams to translate requirements into technical solutions, integrate data from multiple sources, and develop automated pipelines that generate actionable insights.
Responsibilities:
Lead design, development, and optimization of data pipelines to support analytics, AI models, generative AI applications, and business intelligence.
Architect and maintain APIs for seamless data exchange between systems, including Salesforce Data Cloud and Agentforce, enabling AI-powered workflows.
Leverage AI and machine learning to enhance data processing, predictive analytics, and automation.
Implement and integrate large language models (LLMs) and generative AI solutions to improve data insights, automated decision-making, and user experiences.
Provide technical leadership in Salesforce technologies, including APEX code development, Salesforce Flow, and integrations with external data sources and AI services.
Collaborate cross-functionally to implement data governance, security, and compliance best practices.
Optimize data storage, processing, and retrieval in cloud environments, ensuring performance and scalability.
Provide guidance on Salesforce Data Cloud integration and utilization.
Partner with ES teams to define metrics, build proof-of-concepts, and document functional and technical requirements.
Design and develop repeatable automation frameworks supporting AI model training and inference.
Lead review and validation of logical and physical design to align with solution architecture.
Collaborate with data scientists to support data needs and deploy scalable models.
Lead and collaborate with global teams across North America, EMEA, and APAC.
Required Qualifications:
Bachelor’s degree in Computer Science or relevant work experience; 10+ years in data engineering, data modeling, machine learning, automation, and analytics. People Analytics experience is a plus.
Strong expertise in AI/ML, including generative AI, LLMs, NLP, and AI model deployment.
Experience designing AI-driven solutions, including RAG, vector databases, and embedding models.
Proficiency in SQL, Bash, and Python scripting.
Experience with orchestration tools (e.g., Apache Airflow) and version control (GIT).
Solid understanding of data warehousing and data modeling concepts.
Experience integrating systems through APIs.
Experience with AWS technologies (ECS, Aurora, Lambda, S3) preferred.
Experience with Salesforce Data Cloud and Snowflake or similar platforms preferred.
Deep understanding of data engineering concepts, database design, tools, and architecture.
Experience collaborating with Analytics/Data Science teams.
Excellent interpersonal skills; team-first mentality.
Self-starter, highly motivated, able to adapt quickly to shifting priorities and solve complex problems.
Results-oriented, able to work with minimal supervision.
Preferred Qualifications:
Experience with data visualization tools such as Tableau.
Experience working with globally distributed engineering teams.
Exposure to Salesforce technologies (APEX, Salesforce Flow, integrations).
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
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Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
