Data Engineer

We are an executive search firm currently hiring on behalf of our client. Our focus is on identifying professionals whose skills and experience align with our clients' strategic hiring needs. About the Company We are a leading organization in analytics, cloud technologies, and digital engineering, helping global enterprises improve business performance through modern technology solutions. Our team partners with businesses to deliver scalable transformation across analytics, AI, cloud, and engineering, with a focus on measurable outcomes and long-term reliability. This role sits within a collaborative environment where engineering excellence, technical ownership, and modern cloud‑native delivery matter. The team operates at enterprise scale and supports initiatives that influence reporting, business intelligence, AI/ML, and broader data‑driven decision‑making. We value strong technical leadership, practical problem‑solving, and the ability to turn complex data challenges into dependable platforms that support growth. Company Proof Points Works on enterprise‑scale cloud, AI, and analytics transformation programs that have direct business impact. Each solution is expected to improve how data is used for reporting, intelligence, and decision support. Operates in a collaborative global delivery environment where engineering teams partner across functions. Success depends on shared accountability, technical clarity, and consistent delivery standards. Uses modern cloud‑native technologies to build resilient platforms. The focus is on creating scalable systems that support current needs while preparing the organization for future data growth. Company Practices & Ways of Working Strong emphasis on technical leadership, mentoring, and engineering ownership across data platform initiatives. The role expects someone who can raise standards while keeping delivery practical and reliable. Prioritizes cloud‑native delivery, automation, and operational discipline through DevOps, Infrastructure as Code, and CI/CD practices. These levers help improve speed, stability, and maintainability. Values data governance, security, and quality as core design principles rather than afterthoughts. This approach supports trust, compliance, and dependable business use of data. About the Role This role owns the design and delivery of enterprise‑scale AWS data platforms that power analytics, reporting, AI/ML, and business intelligence. The focus is on building dependable data foundations that improve how the business accesses, transforms, and uses information. The Lead AWS Data Engineer will combine hands‑on engineering with technical leadership, guiding teams toward scalable architecture, stronger automation, and higher platform reliability. Success in this role means turning complex data requirements into secure, governed, high‑performing solutions that support both current workloads and future growth. The position requires deep AWS expertise, strong programming and data engineering skills, and the ability to influence delivery standards across engineering teams. Key Responsibilities Own the design and implementation of AWS‑native data platforms that support enterprise analytics and reporting. Ensure the platform is built for scale, reliability, and practical business use. Build and optimize ETL and ELT pipelines using AWS services so data flows are efficient, resilient, and ready for downstream consumption. Improve delivery speed while reducing manual effort and failure points. Architect data lake and lakehouse solutions that create a governed foundation for diverse data use cases. Enable teams to access trusted data for intelligence, AI/ML, and business decision‑making. Lead Spark and distributed processing initiatives to handle large and complex datasets effectively. Improve throughput, performance, and engineering consistency across workloads. Implement data governance, security, and quality standards across the platform. Reduce risk, strengthen trust in the data, and support compliant enterprise usage. Support AI/ML data engineering and feature engineering needs so data assets are ready for advanced analytics. This ensures models and downstream teams can work with reliable, structured inputs. Drive DevOps, Infrastructure as Code, and CI/CD practices to improve automation and deployment discipline. The outcome is faster delivery with better stability and repeatability. Optimize performance, scalability, and reliability across data systems and workflows. Keep the platform efficient as data volumes and business demand grow. Deep hands‑on experience with AWS data services such as S3, Glue, Lambda, EMR, Redshift, Athena, and Lake Formation. These tools should be used to build and govern modern data platforms. Strong Python, PySpark, and SQL skills for developing data pipelines, transformation logic, and performance‑tuned processing. The role depends on clean, maintainable engineering code. Practical experience with Spark, workflow orchestration, and distributed computing for large‑scale processing. You should know how to design jobs that are reliable, efficient, and operationally manageable. Working knowledge of Terraform or CloudFormation for Infrastructure as Code. This supports repeatable environments, better control, and more disciplined cloud operations. Strong understanding of data governance, security, quality, and modern data architecture patterns. These principles must guide platform decisions and delivery choices. Experience supporting AI/ML workloads and feature engineering pipelines. The role requires data foundations that can serve advanced analytics use cases. Familiarity with DevOps practices, CI/CD pipelines, and cloud‑native delivery methods. These capabilities help teams move quickly without sacrificing stability. Additional Plus Experience mentoring engineers or leading technical delivery across data teams. This adds leverage by improving team standards and execution quality. Exposure to lakehouse architecture and enterprise‑scale transformation programs. This helps the candidate contribute faster in complex, evolving environments. Experience in collaborative global delivery setups where cross‑functional coordination is important. This supports smoother execution across multiple stakeholders. What You'll Bring A track record of designing and delivering enterprise data platforms on AWS with clear business impact. You know how to connect architecture decisions to reliability, scale, and analytics outcomes. Strong ownership of end‑to‑end data engineering delivery, including pipeline design, governance, and performance optimization. You balance technical depth with practical execution. The ability to lead technical discussions, mentor engineers, and raise delivery standards across a team. You help others move faster while keeping solutions robust and maintainable. Experience working with modern cloud, analytics, and AI/ML data patterns in fast‑moving environments. You can translate complex requirements into dependable engineering solutions. Why Join Us This is an opportunity to work on enterprise‑scale cloud, analytics, and AI transformation initiatives that have meaningful business impact. The role offers the chance to shape foundational data platforms used for reporting, intelligence, and advanced analytics, while also influencing how engineering teams build for scale and reliability. You will work with modern AWS technologies and collaborate in an environment that values technical leadership, automation, and practical problem‑solving. The work is suited to someone who wants ownership, complexity, and the opportunity to improve how data powers business decisions. If you enjoy building resilient systems, mentoring teams, and creating trusted data foundations, this role provides a strong platform to do that. What We Offer Exposure to enterprise‑scale cloud, AI, and analytics transformation work where engineering decisions directly affect business outcomes. A collaborative global delivery environment that values learning, teamwork, and consistent engineering standards. Continuous learning opportunities, including certifications and career growth, supported by modern cloud‑native technology exposure. The chance to work on resilient, scalable AWS data platforms that support analytics, reporting, and AI/ML initiatives. #J-18808-Ljbffr Athena Executive Search & Consulting (AESC)