Lead Data Engineer

The Lead Data Engineer will be responsible for architecting, building, and optimizing the data pipelines and infrastructure that power International SOS’s mission-critical analytics and operational platforms. This role plays a pivotal part in transforming raw data into structured, reliable, and scalable formats to enable data-driven decision-making across the organization. As a technical leader, you will guide engineering best practices, mentor junior team members, and collaborate closely with cross-functional stakeholders to deliver high-impact data solutions.

• Design, construct, install, and maintain scalable and robust data pipelines
• Integrate data from a wide variety of sources, both structured and unstructured
• Optimize data delivery and re-design infrastructure for greater scalability and performance
• Collaborate with data scientists, business analysts, and product managers to deliver data solutions aligned with business needs
• Develop and maintain data models, databases, and ETL processes
• Ensure data quality, reliability, and integrity across systems
• Participate in data architecture and design reviews
• Assist in implementing data governance and data security best practices
• Monitor and troubleshoot data pipeline issues and performance bottlenecks

• A bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field; master’s degree preferred
• At least eight years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks
• Proven project experience developing and maintaining data warehouses in big data solutions.

Experience & Technical Expertise

• 8+ years of hands-on experience in data engineering or related roles, with a strong foundation in building scalable data solutions.
• Proficient in designing and orchestrating ETL/ELT pipelines across structured and unstructured data sources using tools like AWS Glue, Apache Airflow and DBT
• Deep expertise in big data technologies such as Apache Spark, Kafka, Hadoop, and EMR.
• Strong programming skills in Python, Scala, Java, and familiarity with .NET as needed.
• Skilled in working with relational (SQL, Postgres) and NoSQL (DynamoDB) databases.

Cloud & Data Platforms

• Proven experience with cloud platforms including AWS (S3, Lambda, Redshift, Glue, Step Functions).
• Hands-on knowledge of modern data warehousing solutions such as Redshift, BigQuery, and Teradata.

Data Governance & Security

• Solid understanding of data privacy regulations (e.g., GDPR, HIPAA) and security best practices.
• Experience implementing data governance frameworks, metadata management, and data quality controls.

Analytical & Business Acumen

• Ability to design and deploy data solutions that support AI/ML, business intelligence, and advanced analytics use cases.
• Familiarity with data science tools visualization as MS Fabric, Power BI and Excel.
• Strong problem-solving and debugging skills, with the ability to identify and resolve performance bottlenecks in complex systems.
• Familiarity with data science tools and libraries such as Pandas, NumPy, Scikit-learn, Jupyter, and R.

Collaboration & Communication

• Experience working in agile environments and cross-functional teams
• Excellent interpersonal and communication skills; able to work effectively across technical and non-technical teams.
• Capable of translating business requirements into technical solutions and vice versa, bridging gaps between executives, analysts, and engineering teams.
• Demonstrated ability to influence senior stakeholders and contribute to strategic data initiatives