Lead Data Engineer

Kforce has a client that is seeking a Lead Data Engineer in Miami, FL., The Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. You will provide technical leadership to our data platform engineering team. This is done by helping design and implement our next generation data and analytics platforms and products using Data Engineering best practices.

Responsibilities:

• Design, Build, and Operationalize: Formulate production-grade data engineering solutions for the data and analytics platforms and products
• Pipeline Architecture: Architect and implement reliable ETL, ELT, and streaming data ingestion/delivery processes across multiple enterprise sources
• Modern Python Development: Develop, maintain, and containerize modular data applications and utility scripts using Python, leveraging modern cloud infrastructure
• Scale and Improve Infrastructure: Improve data ingestion architecture, emphasizing data quality, cost-performance, maintainability, and extensibility across storage and compute layers
• Enforce Standards and Downstream Integrity: Define and implement engineering standards for the data team (including code modularization, version control, automated testing, and secure CI/CD workflows); Ensure strict guidelines for schema evolution to safeguard downstream analytics from unilateral changes
• Platform Observability: Instrument data analytics platforms with robust metrics, alerting, and automated monitoring (SLAs/SLOs) to ensure high availability and data trustworthiness
• AI-Driven Productivity: Leverage modern AI-assisted development tools within daily engineering workflows to accelerate code generation, optimize heavy queries, and improve overall delivery speed
• AI/ML Integration: Collaborate with data science teams to design and optimize data layers specifically tailored for Generative AI applications, Retrieval-Augmented Generation (RAG), and LLM frameworks

Strong Technical Experience (3+ to 6+ years) with:

• Advanced Python Development: Writing clean, object-oriented, and production-grade Python code for complex data manipulation, automation, and API communication
• AWS Platform & Containerization: Hands-on experience deploying, managing, and scaling containerized data workloads using AWS ECS (Elastic Container Service) and ECR; Core AWS architecture: S3, IAM, Lambda, EC2, CloudWatch, and CloudTrail; AWS Certification is a strong plus
• Snowflake Data Cloud: Account administration, optimal virtual warehouse clustering strategies, and budget-optimization; Expert feature implementation: Data Sharing, Time Travel, and Zero-copy cloning
• dbt (Data Build Tool): Managing multi-repository dbt projects and configuring dbt Cloud environments; Creating, documenting, and optimizing advanced dbt models and custom macros
• AI-Assisted Engineering & Data Tools: Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, or Claude/OpenAI APIs) to maximize development efficiency; Familiarity with cloud-native AI services (e.g., Snowflake Cortex or AWS Bedrock) for embedding LLM capabilities directly inside the data layer; Exposure to frameworks used for AI data preparation (e.g., LangChain, Vector Databases, or text embedding generation)

• Data Architecture & Enterprise Modeling: Advanced data warehousing concepts, cloud data lakes, and structured multi-layer designs (Bronze, Silver, Gold)
• Advanced Data Transformations: Designing complex operational pipelines, data cleanup, and robust standardization strategies
• Production SDLC & Workflow Best Practices: Rigorous code reviews, end-to-end testing/QA methodologies, and resilient error-handling frameworks
• Data Governance & Security: Implementing enterprise-level role-based access controls (RBAC), data compliance, and secure environments

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.