EY is seeking a skilled Senior Data Operations & Engineering Specialist to join our team. This role offers a unique opportunity to shape your career within a global organization, leveraging EY's supportive culture and advanced technology. You will contribute to building an exceptional experience for yourself and fostering a better working world for all.

This position focuses on designing, developing, and maintaining robust data platforms and ecosystems across AWS and Azure environments. The ideal candidate will possess extensive experience in data integration, cloud-based data engineering, and driving operational excellence.

Join us to make a significant impact by enhancing data capabilities and contributing to innovative solutions.

As a Data Operations & Engineering Specialist, your core responsibilities will include:

- Designing, developing, and maintaining scalable data pipelines and integration frameworks. - Managing and optimizing cloud-based data platforms, databases, data warehouses, and analytical datasets. - Leading and supporting critical data migration, modernization, and transformation initiatives. - Collaborating closely with business, analytics, and reporting teams to ensure the delivery of reliable and trusted data assets. - Upholding high standards for data quality, security, performance, availability, and operational stability. - Providing essential support for BI, reporting, and self-service analytics endeavors. - Continuously monitoring, troubleshooting, and enhancing data platform operations and associated processes.

To excel in this role, you should possess:

- Strong hands-on expertise in SQL, Python, and/or PySpark. - Proven experience in designing and developing ETL/ELT pipelines, data flows, and integration solutions. - Practical experience with AWS services (S3, Glue, Redshift, Lambda, Athena) and/or Azure services (ADF, Databricks, ADLS, Synapse). - Solid understanding of Data Warehousing, Data Lakes, Lakehouse architectures, and dimensional data modeling (Star/Snowflake). - Experience building and supporting enterprise data platforms for reporting, analytics, and business intelligence. - Hands-on experience with data migration and modernization projects, including cloud and legacy platform transformations. - Proficiency with Spark/Databricks and large-scale data processing. - Knowledge of batch and real-time data processing frameworks. - Experience with pipeline orchestration tools like Airflow, ADF, or Step Functions. - A strong grasp of data quality, performance tuning, and operational support. - Experience supporting BI solutions using platforms such as Power BI, Tableau, or QuickSight. - Familiarity with source control, CI/CD, and Agile delivery methodologies.