Senior Manager, Data Engineering

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager, Data Engineering based in United States.** This role offers the opportunity to lead the design and evolution of enterprise-scale data platforms that power analytics, machine learning, and AI-driven solutions. You will combine deep technical expertise with strategic leadership to build secure, scalable, and reliable data ecosystems. Working closely with business stakeholders, data scientists, analysts, architects, and engineering teams, you will transform complex requirements into impactful technology solutions. The position focuses on modern cloud architectures, automation, governance, and continuous improvement across large-scale data environments. You will provide technical direction, mentor engineering teams, and help establish best practices for data engineering excellence. This role is ideal for a technology leader who enjoys solving complex challenges and enabling data-driven decision-making across an organization. With a remote-first environment, you will have the opportunity to influence critical data initiatives while collaborating with multidisciplinary teams. ### Accountabilities: - Lead the design, development, and optimization of modern enterprise data platforms supporting analytics, reporting, machine learning, and AI initiatives. - Architect and implement scalable data solutions, including ETL/ELT pipelines, data models, lakehouse architectures, and cloud-based data platforms. - Translate business requirements into secure, reliable, and high-performing data products that deliver measurable business value. - Partner with data scientists, analysts, architects, engineers, and business leaders to define technical strategies and deliver innovative solutions. - Build and maintain cloud-native data architectures across platforms such as AWS, Snowflake, Azure, Databricks, and related technologies. - Implement data quality frameworks, monitoring solutions, governance practices, security controls, and platform optimization strategies. - Automate infrastructure provisioning and deployment processes using Infrastructure-as-Code tools and DevOps best practices. - Drive technical initiatives, influence architectural decisions, and establish engineering standards across data teams. - Mentor data engineers, conduct code reviews, provide technical guidance, and promote continuous learning and improvement. - Evaluate emerging technologies, including generative AI, machine learning platforms, and automation solutions, to improve data capabilities. - Collaborate within Agile delivery environments to manage projects from concept through implementation, support, and continuous enhancement. - Optimize platform performance, reliability, scalability, and cloud costs while maintaining strong operational standards. ## **Requirements:** - Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field; equivalent professional experience may also be considered. - Master’s degree in Computer Science, Data Science, Information Systems, or a related discipline is preferred. - 10+ years of progressive experience in data engineering, analytics engineering, business intelligence, or related technical roles. - Proven experience designing and delivering enterprise-scale data platforms and analytics solutions. - Strong leadership skills with the ability to influence technical decisions and guide complex engineering initiatives. - Advanced proficiency in SQL and Python. - Hands-on experience building and maintaining scalable ETL/ELT pipelines and distributed data processing solutions using technologies such as PySpark. - Strong understanding of enterprise data modeling, data warehouses, data lakes, and modern lakehouse architectures. - Experience implementing data governance, data quality, monitoring, and security frameworks. - Experience with cloud plat…