The posting
Data Engineering Leadership
- Lead enterprise data integration and modernization initiatives.
- Design and implement cloud-native ETL architectures.
- Drive migration efforts from legacy platforms to modern Data Engineering solutions.
Analytics Enablement
- Partner with BI teams to design scalable reporting and semantic data models.
- Establish best practices for Power BI and Tableau data consumption layers.
- Optimize enterprise reporting performance.
Architecture & Modern Platforms
- Architect end-to-end solutions leveraging:
- Databricks
- Snowflake
- Azure Data Factory
- AWS Glue
- Apache Airflow
- Spark
AI-Driven ETL Modernization
- Drive adoption of AI-enabled development practices.
- Lead ETL migration projects using Generative AI-assisted code conversion and test automation.
- Develop intelligent monitoring, reconciliation, and anomaly detection capabilities.
Leadership & Mentorship
- Establish development standards and governance policies.
- Mentor ETL Developers and ETL Analysts.
- Participate in hiring, technical assessments, and onboarding.
Additional Technical Skills (Senior ETL Developer)
Required
- 7+ years of Data Integration and Data Engineering experience
- Expert in Talend and/or Informatica
- Advanced SQL expertise
- Python and PySpark
- PostgreSQL and Oracle
- Databricks
- Snowflake
- Power BI and Tableau
- Azure Data Factory and/or AWS Glue
- Apache Airflow
- Git, CI/CD, DevOps
Preferred
- Microsoft Azure Data Engineer Certification
- AWS Data Analytics Certification
- SnowPro Certification
- Experience with Collibra, Alation, or Informatica Data Governance
- Experience leading ETL modernization programs



