Senior Data Engineer

Our Company•Seffner, FL

About The Position

This role is designed for a Senior Data Engineer responsible for architecting, developing, and optimizing end-to-end data solutions that support enterprise-scale AI, machine learning, and business intelligence initiatives. With deep expertise in Databricks and cloud-based data platforms, this individual leads high-impact projects, mentors junior team members, and drives innovation across the data engineering function. The Senior Data Engineer plays a key role in enabling data-driven decision-making by ensuring the availability, reliability, and scalability of core data infrastructure.

Requirements

5–7 years of progressive experience in data engineering, with a proven track record of delivering production-grade, cloud-based data solutions
Proficiency in Python, SQL, Apache Spark, and large-scale data processing frameworks
Deep hands-on experience with Databricks, Delta Live Tables, and real-time streaming architectures
Strong understanding of data modeling techniques, including dimensional modeling and star schema design, including implementation patterns for slowly changing dimensions
Proven experience building and managing cloud-based data environments (Azure preferred; AWS/GCP also valuable)
Working knowledge of AI/ML lifecycles to design, build and optimize data pipelines that effectively support model training, feature engineering, data versioning, and low-latency inference needs
Strong grasp of data governance, metadata management, and cloud security best practices
Experience leading the design and execution of enterprise data transformation initiatives and mentoring technical peers
Strong analytical and problem-solving skills with the ability to address complex technical challenges independently
Ability to work effectively in a collaborative team environment and lead technical discussions
Excellent organizational skills with the ability to manage multiple priorities and meet deadlines
Proactive mindset and commitment to continuous learning and technical excellence
Clear and effective written and verbal communication skills
Bachelor’s degree in computer science, data engineering, information systems, or a related field is preferred
Databricks Certified Data Engineer Professional or Microsoft Fabric Data Engineer Associate certification is required (or must be obtained within 6 months)

Nice To Haves

Advanced Databricks certifications (e.g., Machine Learning Professional) are highly desirable

Responsibilities

Architect and implement complex, scalable data pipelines on Databricks using tools such as Delta Live Tables, Structured Streaming, and Apache Spark
Lead the design and optimization of modern Data Warehouse Architectures using Snowflake, star schema modeling, and cloud-native best practices
Collaborate with AI/ML teams to integrate data pipelines for real-time and batch model training, scoring, and monitoring workflows
Serve as a technical lead on cross-functional projects that incorporate predictive analytics, machine learning, and advanced data transformation
Develop and implement data governance frameworks, security standards, and compliance controls across data platforms
Optimize cluster and workflow performance in Databricks to ensure cost-effective and reliable data processing
Mentor and guide mid-level and junior engineers, supporting their development through code reviews, architectural guidance, and knowledge sharing
Stay current with industry trends in data engineering, cloud infrastructure, and AI integrations, and identify opportunities for innovation
Document technical designs, processes, and architectural decisions to promote knowledge reuse and support maintainability
Performs other duties as required