Data Engineer II

Job Description

Job Description

Data Engineer Opportunity

Location & Work Arrangement

• Location: Miami, FL
• Type: On-site / Remote (Hybrid required by end of year)
• Contract Duration: 1+ Year
• Level: Mid-Level (Senior candidates not required)

Role Overview

Join a fast-growing Data Engineering & Analytics team. The role involves developing high-performance data solutions, algorithms, and workflows for vast datasets (billions of transactions) gathered from retail, restaurants, banks, and consumer-focused companies. You will work with front-end visualizations and machine learning techniques to drive business insights.

Key Responsibilities

• Data Architecture & Engineering: Design data architecture/schema, build automated data pipelines, and optimize machine learning frameworks.
• Machine Learning & AI: Design ML systems and AI software to automate predictive models; ensure algorithm accuracy for user recommendations.
• Data Processing: Transform unstructured data into useful information (e.g., auto-tagging images, text-to-speech); handle real-time, streaming, batch, and API-based data ingestion.
• Problem Solving: Solve complex problems with multi-layered datasets and optimize existing libraries.
• Collaboration: Advise Data Scientists and consumers on data issues, partner with cross-functional teams (engineering, sales, consultants) to prioritize problems, and evaluate trade-offs for analytics solutions.
• Data Governance: Implement and validate data lineage, quality checks, and classification policies.
• Innovation: Experiment with new tools to streamline pipeline development/testing and continuously identify new technical approaches.
• Project Management: Break large solutions into releasable milestones, incorporate stakeholder feedback, and track usage metrics.
• Maintenance: Maintain awareness of technical trends and escalate technical errors/bugs.

Technical Skills & Tools

• Languages: Python, R
• Big Data Execution Engines: Hive, Impala, Spark
• Areas of Expertise: Machine Learning, Artificial Intelligence, Data Architecture, Data Lineage, Big Data Optimization