Senior EM Data Engineering

Summary

Join Globalization Partners as a Senior Engineering Manager and lead geographically distributed engineering teams in designing and delivering complex data and analytics platforms. You will own the strategic direction and execution of initiatives across the Data Platform, guiding teams through architectural decisions and complex program execution. Lead and grow high-performing engineering teams responsible for the full data and analytics stack, ensuring quality, reliability, and performance at scale. Partner with various stakeholders to shape product and platform capabilities, translating business needs into actionable engineering plans. Drive delivery excellence, ensure adoption of platform standards, and support technical leadership across teams. Contribute to strategic planning and champion agile methodologies and DevOps practices. Mentor and develop engineering talent, fostering a culture of innovation and accountability.

Requirements

• Proven experience leading geographically distributed engineering teams in the design and delivery of complex data and analytics platforms
• Strong technical foundation with hands-on experience in modern data architectures, handling structured and unstructured data, and programming in Python—capable of guiding teams and reviewing design and code at a high level when necessary
• Proficiency in SQL and relational database technologies , with the ability to guide data modeling and performance optimization discussions
• In-depth understanding of ETL processes and data integration strategies , with practical experience overseeing data ingestion (batch and streaming), transformation, and quality assurance initiatives
• Familiarity with commercial data platforms (e.g., Databricks, Snowflake) and cloud-native data warehouses (e.g., Redshift, BigQuery), including trade-offs and best practices in enterprise environments
• Working knowledge of data governance and cataloging solutions , such as Atlan, Alation, Informatica, or Collibra, and experience supporting enterprise data stewardship efforts
• Deep understanding of data quality , experience in building quality processes, and usage of tools like Monte Carlo
• Understanding of machine learning and AI workloads , including the orchestration of data pipelines for model training and deployment in both batch and streaming contexts
• Strong analytical and problem-solving skills , with the ability to drive root-cause analysis, evaluate architectural trade-offs, and support decision-making in ambiguous or fast-changing environments
• Exceptional communication skills , with a track record of clear and effective collaboration across technical and non-technical stakeholders
• Fluent in English , both verbal and written, with the ability to influence at all levels of the organization
• Bachelor’s degree in Computer Science or a related field ; advanced degrees or equivalent professional experience are a plus

Responsibilities

• Own the strategic direction and execution of initiatives across our Data Platform , aligning technical vision with business goals
• Guide teams through architectural decisions, delivery planning, and execution of complex programs that advance our platform capabilities
• Lead and grow high-performing engineering teams responsible for the full data and analytics stack—from ingestion (ETL and Streaming) through transformation, storage, and consumption—ensuring quality, reliability, and performance at scale
• Partner cross-functionally with product managers, architects, engineering leaders, and stakeholders from Cloud Engineering and other business domains to shape product and platform capabilities, translating business needs into actionable engineering plans
• Drive delivery excellence by setting clear expectations, removing blockers, and ensuring engineering teams are progressing efficiently towards milestones while maintaining technical integrity
• Ensure adoption and consistency of platform standards and best practices , including shared components, reusable libraries, and scalable data patterns
• Support technical leadership across teams by fostering a strong culture of engineering excellence, security, and operational efficiency
• Guide technical leads in maintaining high standards in architecture, development, and testing
• Contribute to strategic planning , including the evolution of the data platform roadmap, migration strategies, and long-term technology investments aligned with company goals
• Champion agile methodologies and DevOps practices , driving continuous improvement in team collaboration, delivery cycles, and operational maturity
• Mentor and develop engineering talent , creating an environment where individuals can thrive through coaching, feedback, and growth opportunities
• Promote a culture of innovation, accountability, and psychological safety
• Challenge the Data Platform Quality and Performance by building/monitoring quality KPI and building a quality-first culture

Benefits

Competitive compensation and benefits