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Data Engineer

Remote

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

  • Drive automation and scalability by utilizing AI/ML tools and automated data pipelines to enhance data migration, cleansing, and transformation processes.
  • Ensure enterprise-wide data integrity through rigorous quality assessments, cleansing, and deduplication, maintaining a high standard of reliability.
  • Mitigate data-related risks by proactively identifying and resolving issues that could impact operational accuracy and decision-making.
  • Lead data mapping and integration efforts, collaborating across functions to ensure seamless data alignment and migration during M&A activities.
  • 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 strong 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, or 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 business intelligence 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.

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