Head of Data Engineering

Job not on LinkedIn

October 27

Apply Now

Receive Emails with Similar Jobs

GoGlobal

WebsiteLinkedInAll Job Openings

HR Tech • Enterprise • Compliance

GoGlobal is a leading provider of global human resources management solutions, specializing in services such as global hiring, employee onboarding, payroll management, and compliance with international regulations. As an Employer of Record (EOR), GoGlobal allows businesses to hire and manage talent worldwide without the complexities and legal risks involved in international employment. Their platform enables clients to attract, hire, and retain the best talent while ensuring compliance with local labor laws across various countries. By offering expert HR consulting and support, GoGlobal helps companies expand globally, explore new markets, and manage transactions smoothly. The company is committed to providing comprehensive HR solutions that facilitate global business operations, making it easier for businesses to thrive internationally.

51 - 200 employees

👥 HR Tech

🏢 Enterprise

📋 Compliance

📋 Description

• Build and scale the data engineering organization from inception to a fully operational, high-performing team • Define and execute the data strategy aligned with business objectives and long-term growth • Establish the technical vision and roadmap for data infrastructure, tools, and platforms • Partner with executive leadership to identify data opportunities that drive business value • Build strong relationships with stakeholders across Engineering, Product, Analytics, Data Science, and Business teams • Design and implement a scalable, reliable data lake architecture from scratch • Build robust ETL/ELT pipelines for data ingestion, transformation, and distribution • Establish data orchestration frameworks for workflow management and scheduling • Architect solutions for real-time and batch data processing at scale • Ensure high availability, performance, and cost optimization of data systems • Implement comprehensive data governance frameworks and policies • Establish data quality standards, monitoring, and validation processes • Design and enforce data security, privacy, and compliance measures (GDPR, CCPA, etc.) • Create data cataloging and metadata management solutions • Build data lineage and audit trail capabilities • Evaluate, select, and implement modern data platforms (Snowflake, Databricks, Google BigQuery) • Build self-service data capabilities for analytics and data science teams • Establish CI/CD practices for data pipelines and infrastructure as code • Implement monitoring, alerting, and observability for data systems • Drive adoption of best-in-class data tools and technologies • Recruit, mentor, and develop a high-performing data engineering team • Foster a culture of technical excellence, collaboration, and continuous improvement • Establish career development frameworks and growth paths for team members • Promote best practices in software engineering within the data context • Build strong cross-functional relationships and promote data literacy • Partner with analytics teams to deliver reliable, accessible data products • Enable data science initiatives through robust feature engineering and ML infrastructure • Build data models and transformations that support business intelligence needs • Ensure data democratization while maintaining governance and security

🎯 Requirements

• 8+ years of experience in data engineering, with at least 5 years in leadership roles • Had leadership roles in 1000+ people companies • Proven track record of building a data organization from zero to production scale • Demonstrated experience establishing data lakes, ETL pipelines, and data infrastructure from scratch • History of successfully managing complex data projects with multiple stakeholders • Experience scaling data systems to handle significant data volume and user growth • Expert-level experience with at least one of: Snowflake, Databricks, or Google BigQuery (required) • Strong software engineering fundamentals: data structures, algorithms, design patterns, testing • Proficiency in modern programming languages (Python, Scala, Java, or Go) • Deep understanding of distributed systems and big data technologies (Spark, Kafka, Airflow, Airbyte, dbt) • Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code • Strong SQL skills and deep understanding of database systems (relational and NoSQL) • Experience with data modeling, dimensional modeling, and data warehousing concepts • Hands-on experience implementing data governance frameworks • Understanding of data privacy regulations (GDPR, CCPA, HIPAA, etc.) • Experience with data security, access controls, and compliance auditing • Knowledge of data quality frameworks and data observability tools • Excellent stakeholder management skills across technical and non-technical audiences • Proven ability to translate complex technical concepts into business value • Strong written and verbal communication skills • Experience building and mentoring high-performing engineering teams • Track record of fostering inclusive, collaborative team cultures • Experience with real-time data streaming and event-driven architectures • Knowledge of machine learning operations (MLOps) and feature stores • Familiarity with data mesh or domain-driven data architecture patterns • Experience with DataOps practices and automation • Contributions to open-source data projects • Advanced degree in Computer Science, Engineering, or related field • Experience in [relevant industry: fintech, healthcare, e-commerce, etc.]