Project - Data Engineer II

Experteer Overview You will design, build, and operate scalable data pipelines and curated datasets to enable analytics and downstream applications. In the Data & Analytics Foundry, you'll work with cross-functional teams across onshore/offshore delivery to implement reliable and cost-efficient data solutions on cloud platforms. The role combines hands-on engineering with engagement leadership to transform client data landscapes. You will optimize data architecture, promote best practices, and contribute to the delivery of modern data products. This opportunity offers high-impact work within Deloitte's Project Delivery Model and a chance to influence data strategy for multiple clients. Compensation / Benefits * Design, build, and support scalable batch and near-real-time data pipelines on AWS * Ingest data from sources into S3 and Snowflake, with robust patterns * Develop transformations and curated datasets in Snowflake with dimensional modeling * Implement orchestration and workflow automation on AWS with retries and idempotency * Create reusable Python components for ingestion, validation, and transformations * Optimize Snowflake performance and cost (warehouses, concurrency, tuning, clustering) * Collaborate with stakeholders to translate requirements into datasets and data contracts * Lead client engagement workstreams focused on process improvement and transformation Tasks * 4+ years delivering production-grade data pipelines and curated datasets * 4+ years with SQL and Python, Snowflake and/or PySpark for scalable processing * 4+ years designing/building data pipelines on cloud platforms (AWS preferred; Azure/GCP acceptable) * Experience with data integration frameworks and orchestration tools * Knowledge of Lakehouse/warehouse architectures and ELT patterns * Knowledge of DevOps: CI/CD, version control, Infrastructure-as-Code * Ability to optimize data storage, partitioning, file formats (Delta, Parquet), and performance * Understanding of data quality, governance, and metadata management * Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline Key requirements *

automation on AWS with retries and idempotency * Create reusable Python components for ingestion, validation, and transformations * Optimize Snowflake performance and cost (warehouses, concurrency, tuning, clustering) * Collaborate with stakeholders to translate requirements into datasets and data contracts * Lead client engagement workstreams focused on process improvement and transformation Tasks * 4+ years delivering production-grade data pipelines and curated datasets * 4+ years with SQL and Python, Snowflake and/or PySpark for scalable processing * 4+ years designing/building data pipelines on cloud platforms (AWS preferred; Azure/GCP acceptable) * Experience with data integration frameworks and orchestration tools * Knowledge of Lakehouse/warehouse architectures and ELT patterns * Knowledge of DevOps: CI/CD, version control, Infrastructure-as-Code * Ability to optimize data storage, partitioning, file formats (Delta, Parquet), and performance * Understanding of data quality, aaaaa client and metadata management * Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline Key requirements *