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 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.
