The Data Engineer will manage the design, automation, and governance of enterprise-wide data flows, ensuring that core business data is accurate, consistent, and accessible across the organization. This role will play a pivotal part in scaling and optimizing data processes that power business operations, partnering with cross-functional leaders to drive data integrity, automation, and AI-driven efficiencies.

This individual will architect and maintain data structures, leveraging automated pipelines, AI, and cloud-native tools to ensure that data migrations for acquired businesses are rapid, accurate, and seamlessly integrated. During acquisition integrations, the Data Engineer will work cross-functionally to identify key data sources, map them into standardized structures, and automate migration processes, ensuring data is cleansed, validated, and optimized for strategic decision-making.

Key Responsibilities

• Automate and scale data processes using AI/ML tools and automated pipelines to enhance data migration, cleansing, and transformation.
• Ensure enterprise-wide data integrity through rigorous quality assessments, cleansing, and deduplication.
• Identify and mitigate risks by proactively addressing data-related issues that could impact business operations.
• Lead data mapping and integration efforts, collaborating across functions to ensure seamless M&A data consolidation and migration.
• Architect scalable data solutions leveraging cloud-native technologies (AWS, Azure, Google Cloud) to optimize performance and security.
  
  

Competencies

• Attention to detail: Involves a meticulous approach to work, prioritizing accuracy and thoroughness to ensure high-quality outcomes
• Proactive problem solving: Ability to identify potential issues before they arise and effectively address them to mitigate risks and capitalize on opportunities
• Technical aptitude: Demonstrates strong technical aptitude to solve business challenges
• Data analysis and reporting: Utilizes data analysis skills to support business decisions and reporting
• M&A and integration: Manages M&A processes to ensure smooth transitions and integration
  
  

Qualifications

• 3+ years of experience in data engineering, business systems, or data science with a focus on automation and data optimization.
• Proficiency in ETL/ELT tools such as Apache Airflow, Talend, AWS Glue, or other cloud-native data pipeline solutions.
• Expertise in cloud platforms (AWS, Azure, Google Cloud) for data storage, processing, and security.
• Strong programming skills in Python, Java, or Scala, with experience in data transformation and automation.
• Deep knowledge of relational databases and data governance best practices.
• Experience with data visualization and BI tools to enable effective reporting and insights.
  
  

Preferred

• Experience leading data integration efforts during M&A transactions, ensuring efficient data consolidation and migration.
• Professional certifications in cloud platforms or data engineering technologies.
• Strong stakeholder management skills, with the ability to translate complex data challenges into clear business solutions.