Hiring: Forward Deployed Data Engineer Company: Perform Location: Nashville, TN Job Posted Time: 2026-09-15 11:05:49 Employment Type: Hybrid Target Skills & Keywords : Azure, Data Pipeline, Databricks, Delta Lake, ETL, LLM, PySpark, Python, RAG, SQL, SQL Server, Salesforce, Snowflake, Spark, User Experience About the job Required Skills: •The data engineer role has changed. Building a pipeline, handing it off, and waiting for someone else to confirm the data is right no longer creates much value. The engineers who matter now go deep into the business domain, understand the problem directly, and use AI tools to move from question to working solution in hours rather than sprints. •This is what it means to shift the engineer left into the business. You are not a pipeline builder waiting on a ticket. You are the person who understands how physician network growth, member engagement, and operational performance actually work, and who builds the data infrastructure that makes the entire analytics function faster and sharper. •This position supports a healthcare organization, so US residency is required and experience handling regulated data is valued. •Design, build, and operate the data platform on Azure Databricks, covering ingestion, transformation, storage, and serving layers that power analytics, AI models, and operational reporting. •Build and maintain pipelines across the business ecosystem, including Salesforce, SQL Server, Snowflake, third-party sources, and a new cloud-native payments platform. •Engineer for quality and trust through validation checks, anomaly detection, lineage tracking, and documentation that every downstream consumer can rely on. •Write clean, version-controlled, production-grade code. Think like a software engineer building a product, not a script runner maintaining jobs. •Own architecture decisions across storage, transformation, orchestration, and serving, balancing delivery speed against long-term maintainability. Qualifications: •A data engineer who refuses to stay in the technical silo. You go find the business problem rather than waiting for it to arrive as a ticket. •Someone who thinks like a product owner. You prioritize by impact, ship incrementally, and own the outcome, not just the pipeline. •The kind of engineer who was already using AI tools to write, test, and deploy code before anyone asked, and who knows when the output needs a human eye. •Equally comfortable writing a Spark transformation, debugging a Salesforce data sync, presenting findings to leadership, and pushing back on a vague requirement. •Pragmatic over perfectionist. You optimize for business impact and speed to value rather than theoretical elegance. •A strong collaborator who elevates the people around you through clear communication, reusable patterns, and generous knowledge sharing. •BS in Computer Science, Data Science, or a related field, with 6 or more years in data engineering or a hybrid data engineering and analytics role. •Deep hands-on experience with Azure Databricks, including notebooks, Delta Lake, Unity Catalog, and production-scale pipelines. •Strong Python and SQL, with experience in PySpark and distributed data processing. •Direct experience working with business stakeholders to define requirements, shape data products, and deliver measurable outcomes. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!