Data Engineer

Job Role: Senior Data Engineer / AI/ML Engineer (Agentic) Location: Remote (United States) Job Type: W2 Contract Position Overview Client is building a new team within the UKS Data Strategy & Operations function focused on transforming Data 360 into high-value, actionable insights through agent-driven enrichment. This role sits within the Enrichment Platform & Agents workstream, where engineers will design and build intelligent, agentic data systems that automate ingestion, validation, enrichment, and delivery of third-party data to internal stakeholders and core Salesforce platforms. Scope of Work • Build agentic capabilities to improve operational efficiency in third-party data ingestion and consumption • Develop and manage data pipelines that ingest, enrich, and distribute data across systems • Manage data egress from Data 360 to downstream platforms, including Salesforce CRM • Reduce manual operational processes through automation and intelligent workflows Key Responsibilities • Design and develop scalable ETL pipelines using Informatica, Python, and SQL • Build and manage batch and real-time data pipelines across distributed systems • Develop integrations using Airflow (orchestration) and MuleSoft (API/integration layer) • Build and maintain data ingestion pipelines from third-party providers • Own pipeline monitoring, troubleshooting, and optimization • Implement data transformation and modeling using dbt • Enable data egress patterns to deliver outputs to multiple downstream systems • Track KPIs including data volume, pipeline performance, and ingestion success rates • Collaborate with Product, Data Science, and Analytics teams for data consumption needs Must-Have Skills • Strong experience in Data Engineering, ETL, and Data Architecture (Informatica preferred) • Hands-on experience with Python, SQL, ETL frameworks, Airflow, Salesforce, and MuleSoft • Strong experience with Snowflake or similar relational databases • Experience building complex Python-based ETL modules and workflows • Expertise in building batch and real-time data pipelines • Experience with dbt for transformations and data modeling • Familiarity with AWS and/or GCP environments • Strong understanding of distributed systems and event-driven architectures • Expertise in data modeling, data warehousing, and large-scale data processing • Experience with data quality, monitoring, and orchestration frameworks AI / Agentic Engineering Requirements • Strong Python experience for AI/ML and application development • Experience working with LLM APIs (OpenAI, Anthropic, Gemini) beyond basic use cases • Hands-on experience with agentic frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar • Experience building RAG pipelines and working with vector databases (Pinecone, Chroma, Milvus) • Strong system design mindset — ability to decompose complex workflows into autonomous agent tasks Preferred Skills • Experience building multi-agent systems or multi-step autonomous workflows • Exposure to Model Context Protocol (MCP) integrations • Experience working with multi-modal agents (text, document, image processing) • Experience with Salesforce Flows and Apex Day-to-Day • Build and onboard new data integrations into Data 360 • Develop agent-driven workflows to automate ingestion and enrichment processes • Monitor pipeline performance and resolve production issues • Drive data distribution to downstream platforms including Salesforce CRM • Continuously optimize data workflows and reduce manual interventions First 30 Days / Near-Term Priorities • Conduct deep discovery on a high-priority agentic use case and deliver an initial POC • Begin productizing agent-driven workflows to improve operational efficiency • Reduce manual validation and ingestion processes through automation • Support integration and management of third-party data sources Why This Role This is a high-impact opportunity to work on cutting-edge agentic AI + data engineering initiatives within Salesforce, driving automation, scalability, and next-generation data operations for enterprise platforms. Must haves: 1. Python 1. Mulesoft/airflow 1. SQL/ETL 1. Infomatica cloud 1. Working on salesforce platform building data on top