Senior Data Engineer

We are looking for a senior data engineer to design, develop, and optimize scalable, reliable, and high-performance data platforms and pipelines. The ideal candidate will have strong hands-on experience in Snowflake, AWS Glue, PySpark/Python, SQL Server/T-SQL, Fivetran, and modern ETL/ELT architecture.
Key Responsibilities
Design and develop scalable ETL/ELT, data ingestion, transformation, and integration pipelines across multiple source systems.
Build and maintain data warehouses, data marts, and scalable data models using modern data engineering and dimensional modeling principles.
Develop and optimize complex SQL solutions using Snowflake and SQL Server/T-SQL.
Develop scalable AWS Glue jobs using PySpark/Python, including transformation, partitioning, and performance optimization.
Design and maintain data ingestion and replication pipelines using Fivetran, including monitoring and schema change management.
Implement incremental loading and Change Data Capture (CDC) strategies for large-volume data processing.
Optimize Snowflake performance and cost, including query performance, warehouse sizing, data models, and resource utilization.
Implement data quality, validation, reconciliation, monitoring, logging, alerting, and error-handling mechanisms.
Investigate and resolve complex data pipeline, data quality, SQL, performance, and production issues, including root cause analysis.
Contribute to technical architecture, design decisions, engineering standards, code reviews, testing, deployment, and documentation.
Collaborate with Data Analysts, BI Developers, Architects, Engineers, and business stakeholders to deliver reliable data solutions.
Skills & Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Engineering, IT, Engineering, or a related field.
5+ years of professional experience in Data Engineering, ETL/ELT, Data Warehousing, or a related field, with senior-level responsibilities.
Strong hands-on experience with Snowflake, including data modeling, SQL, performance optimization, security, and cost optimization.
Strong hands-on experience with AWS Glue and PySpark/Python for production-grade data processing.
Strong experience with SQL Server/T-SQL, including complex queries, stored procedures, CTEs, window functions, indexing, query optimization, and performance troubleshooting.
Practical experience with Fivetran or similar data integration/replication platforms.
Strong understanding of ETL/ELT architecture, data warehousing, dimensional modeling, data marts, incremental loading, CDC, and data pipeline design.
Good knowledge of AWS data services including S3, IAM, CloudWatch, Lambda, and Secrets Manager.
Experience with Git, CI/CD, code reviews, automated testing, monitoring, and production support.
Strong problem-solving, analytical, communication, and stakeholder collaboration skills.
Experience working in Agile/Scrum environments.
Must-Have Technical Skills
Snowflake | AWS Glue | PySpark/Python | SQL Server/T-SQL | Fivetran | ETL/ELT | Data Warehousing | Data Modeling | Dimensional Modeling | CDC | Incremental Loading | AWS S3/IAM/CloudWatch
Good to Have
Experience with Machine Learning model development, deployment, monitoring, and the end-to-end ML lifecycle.
Experience with scikit-learn, TensorFlow, or similar ML frameworks.
Experience integrating ML/data science workflows with cloud data platforms and production pipelines.
Experience with Power BI, including DAX, Power Query, data modeling, and performance optimization.
Experience developing Streamlit dashboards and data applications using Python.
Understanding of how Data Engineering, BI, Analytics, and Machine Learning integrate within a modern data platform.
If you believe you are the right fit, please send your CV to hello@aventude.com. Once submitted, your resume will be retained in our database for a period of 6 months. If you have any questions or concerns regarding your application or data retention, please feel free to contact us at hello@aventude.com

Work arrangement
Yes