Senior Data Engineer

Designs and develops data models and data pipelines to enable efficient data collection and processing from diverse data sources. Implements data governance policies and procedures for data handling to manage data consistency, integrity, accuracy, security, and reliability. Implements rigorous data validation and integrity checks to support data pipeline and model performance. Designs, develops, and optimizes automated and scalable data pipeline architectures to build data products, independently. Collaborates in an agile development environment to develop, maintain, and debug data solutions that are scalable, efficient, and reliable.

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Key Responsibilities

Data Processing & Pipelining – Data Requirements, Collection, and Infrastructure:

• Analyzes business requirements

  
  

• Analyzes data sources to ensure successful data extraction and pipeline development.

  
  

• Designs data models for optimal data processing and reporting performance.

  
  

• Designs and implements data pipelines for optimal data processing.

  
  

• Conducts comprehensive testing of deliverables to ensure quality, accuracy, and reliability.

  
  

• Identifies, analyzes, and troubleshoots data issues, such as mismatches, refresh errors, and inconsistencies.

  
  

• Analyzes deployment statistics, customer feedback, and platform enhancements to identify and drive product improvements.

  
  

Data Processing & Pipelining – Data Governance: 

• Implements data governance policies and procedures for data handling (e.g., data retention) to manage data consistency, integrity, accuracy, and reliability throughout the data lifecycle.

  
  

• Redacts Personally Identifiable Information (PII) and Protected Health Information (PHI) data to ensure compliance with data privacy and security standards.

  
  

• Follows data security measures to protect data from unauthorized access, use, disclosure, alteration, or destruction.

  
  

• Ensures data compliance with relevant laws, regulation, and industry standards.

  
  

Data Processing & Pipelining – Data Validation & Quality Assurance: 

• Implements rigorous data validation and integrity checks, identifying and addressing any data quality issues that could impact data pipeline and model performance.

  
  

• Designs and implements automation of data validation and governance.

  
  

Data Pipeline and Solutions Engineering – Pipeline Design: 

• Independently designs, develops, and optimizes automated and scalable data pipeline architectures to build data products.

  
  

• Implements appropriate data storage solutions to store the processed data to be used in a scalable and optimized way for access and analysis.

  
  

• Manages the flow of data pipeline and storage day-to-day operations.

  
  

Data Pipeline and Solutions Engineering – Data Solutions Engineering: 

• Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug data solutions that are scalable, efficient, cost effective, and reliable.

  
  

Core Responsibilities

Planning & Execution:

• Independently manages work, monitoring timelines and deliverables to ensure projects or initiatives stay on track and meet requirements.

  
  

• Proactively prioritizes work and adapts to resource or timeline shifts, suggesting adjustments to maintain project efficiency.

  
  

Collaboration & Partnership:

• Collaborates across teams to align on expectations and achieve shared objectives.

  
  

• Builds and maintains a comprehensive understanding of business, stakeholder, and/or customer needs to build and support effective partnerships.

  
  

• Actively listens to diverse perspectives and asks questions to ensure understanding of others.

  
  

Problem Solving:

• Independently identifies and addresses standard and non-standard issues in accordance with standard practices, escalating more complex issues as appropriate.

  
  

• Analyzes data and/or information from multiple sources to troubleshoot standard and non-standard errors.

  
  

• Contributes to knowledge sharing and best practices.

  
  

Continuous Learning:

• Embraces continuous learning by actively seeking to build knowledge and new skills and/or tools and staying current with industry trends and best practices.

  
  

• Seeks out and leverages feedback and training to improve skills.

  
  

• Contributes to a culture of continuous learning and knowledge sharing with team members.

  
  

Continuous Improvement:

• Develops ideas and recommends updates to increase the efficiency and effectiveness of processes, protocols, and workflows within a team.

  
  

• Seeks input from team members on alternative approaches and methods for improving work.

  
  

Career Level - IC3