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 Data360 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 Data360 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.

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.
Proficiency with SQL, Python, Informatica IICS, and dbt.
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 (EC2, Aurora, Lambda, S3) preferred.
Experience with Salesforce Data360 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.

Employee Success Lead, Data Engineer

Key skills