Data Engineer II

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)

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.

• 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 escalated technical errors/bugs.

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