Senior Data Engineer

Design, build, and maintain scalable ELT data pipelines on cloud data platforms including Oracle Autonomous Data Warehouse, Snowflake, and Azure Synapse.

Convert legacy ETL pipelines (SSIS, PL/SQL, Informatica) to modern ELT frameworks using dbt, ADF, or equivalent tooling.

Design data models — dimensional, vault, or flat — aligned to business reporting and AI consumption requirements.

Implement data quality checks, lineage tracking, and monitoring across all pipeline layers.

Build and maintain CI/CD pipelines for data engineering — including version control, automated testing, and deployment automation.

Collaborate with data architects, analytics engineers, and client stakeholders to translate business requirements into data engineering solutions.

Support the development of AI-readiness data infrastructure including vector stores and feature engineering pipelines.

Skills & Experience Required

5+ years of hands-on data engineering experience on cloud platforms

Strong SQL and Python skills; experience with dbt, Spark, or equivalent transformation frameworks.

Hands-on experience with at least one of: Oracle ADW, Snowflake, Azure Synapse, or AWS Redshift.

Experience migrating legacy ETL to modern ELT and documenting business logic through reverse engineering.

Knowledge of DataOps practices including version control (Git), automated testing, and CI/CD for data pipelines.