Описание

Design, develop, and maintain scalable data pipelines and integration solutions using Snowflake and AWS
Build and optimize ETL/ELT processes to integrate data from multiple enterprise systems
Develop and maintain data models, schemas, and transformation logic within Snowflake
Implement data transformations, mappings, and business rules
Develop and optimize complex SQL queries and data processing workflows, ensuring performance, scalability, and cost efficiency
Implement data quality controls, validation mechanisms, and reconciliation processes
Collaborate with business and technical stakeholders to translate data requirements into reliable, production-ready implementations
Support secure and controlled data processing practices, particularly when handling sensitive customer and financial information
Implement monitoring, troubleshooting, and continuous improvement practices for data pipelines and integration workflows
Contribute to CI/CD processes, technical documentation, and data engineering best practices.

Strong professional experience in Data Engineering, with a focus on enterprise data integration, transformation, and cloud-based data platforms
Extensive hands-on experience with Snowflake, including data ingestion, transformation, data modeling, and performance optimization
Advanced SQL skills, including complex queries, analytical functions, stored procedures, and query optimization
Solid experience with AWS cloud services
Strong understanding of ETL/ELT architectures, data warehousing concepts, and enterprise data integration patterns
Good understanding of relational and dimensional data modeling, data warehouse design principles, and analytical data structures
Experience implementing data quality checks, reconciliation processes, and data validation mechanisms
Understanding of data security, access controls, and data protection principles when working with sensitive or regulated information
Familiarity with Git-based development workflows, CI/CD pipelines, and automated deployment practices
Strong analytical, troubleshooting, and problem-solving skills
Ability to work independently, take ownership of technical deliverables, and collaborate effectively with technical and business stakeholders

Hands-on experience with dbt (data build tool) for SQL-based transformations, data modeling, testing, and documentation
Experience with Oracle Data Integrator (ODI), including developing, maintaining, or migrating enterprise ETL workflows
Knowledge of Python for data processing, automation, and pipeline development
Experience with orchestration tools such as Apache Airflow

Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus
Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership
Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences
Hybrid work and flexible working hours, employee assistance programme
Global internal wellbeing programme, access to wellbeing apps
Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations

Senior Data Engineer (Snowflake and AWS)