Senior Data Engineer

Summary

Join our growing team as a Senior Data Engineer to develop production-ready data models, integrate multiple data sources, and ensure business requirements are fulfilled throughout the entire data & analytics lifecycle.

Responsibilities

• Design, develop, and implement robust data models for enterprise systems and external sources, ensuring data is accessible, accurate, and consistently available for analysis
• Act as a technical resource in executing data strategies and architectures, collaborating closely with data architects and stakeholders to ensure alignment
• Advocate and adhere to software and data engineering best practices, leveraging cloud technologies to accelerate innovation
• Partner with data architects, product teams, and business experts to create and execute a data management roadmap aligned with company objectives
• Develop tactical solutions to meet immediate needs, while supporting long-term data architecture standards and vision
• Collaborate across teams, including IT, Business Intelligence, Data Quality, and Data Governance, to ensure accurate data metadata and high standards of data quality
• Contribute to solution proposals with vendors and cloud providers, supporting the evaluation and selection of data solutions that meet company and client objectives
• Plan and participate in initiatives for data security, backup, disaster recovery, and business continuity, aligning with best practices for data integrity and regulatory compliance
• Drive best practices in data engineering workflows, from SDLC processes to source control and change management
• Conduct peer reviews, mentoring team members to promote high standards and continuous improvement
• Explore and implement tools and technologies to advance Data Ideology’s data engineering capabilities
• Ensure efficient data mapping, movement, and integration across platforms, maintaining data quality and consistency
• Support project managers and business leads on data-centric initiatives, facilitating successful data integration and system compatibility
• Contribute to cloud cost optimization, data reuse, and tech-debt reduction, promoting sustainable data engineering practices
• Regularly update and enhance the data architecture to keep up with evolving technologies and business needs