Senior Data Engineer

Experteer Overview As a Senior Data Engineer at Deloitte, you will shape data platforms for client delivery within the Project Delivery Model. You will work closely with engagement managers and cross-functional teams to design and optimize large-scale data pipelines. You’ll lead discussions with client architects, implement end-to-end data solutions, and mentor junior engineers. This role offers the chance to work with cutting-edge technologies and drive meaningful impact in a collaborative, client-focused environment. Compensation / Benefits * Communicate with engagement managers and cross-functional teams, escalating matters as needed * Design, develop and optimize ETL/ELT pipelines using Azure Data Factory and Databricks * Write and tune PySpark / Spark SQL notebooks for large-scale transformations * Architect end-to-end data solutions across dev/UAT/prod with Unity Catalog * Lead design discussions with client architects and counterparts * Collaborate on data contracts and schema agreements * Lead design and optimization of high-volume data pipelines * Define and enforce data engineering standards (naming conventions, partitioning, cluster configs, Spark tuning) * Drive performance optimization (AQE tuning, liquid clustering, broadcast joins, shuffle partition management) * Design Databricks cluster policies, autoscaling configurations, and cost optimization * Conduct root cause analysis on production incidents and implement fixes * Mentor junior and mid-level engineers via code reviews and pair programming * Evaluate new technologies and recommend adoption (e.g., DABs, DLT, Auto Loader, Serverless Compute, event hubs) Tasks * Python, PySpark, Spark SQL, SQL Server * Azure (ADF, ADLS Gen2, Key Vault, Azure Monitor) * Databricks (Delta Lake, Unity Catalog, Workflows) * Apache Airflow * Git / Azure DevOps * Deep Spark internals (DAG optimization, spill analysis, skew handling) * Delta Lake advanced features (time travel, deletion vectors, predictive I/O) * Unity Catalog governance (row/column security, external locations, system tables) * IaC - Terraform, Azure ARM templates * Bachelor’s degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience * Limited immigration sponsorship may be available * Ability to travel 10%, on average, based on work and clients served Key requirements *

• agreements * Lead design and optimization of high-volume data pipelines * Define and enforce data engineering standards (naming conventions, partitioning, cluster configs, Spark tuning) * Drive performance optimization (AQE tuning, liquid clustering, broadcast joins, shuffle partition management) * Design Databricks cluster policies, autoscaling configurations, and cost optimization * Conduct root cause analysis on production incidents and implement fixes * Mentor junior and mid-level engineers via code reviews and pair programming * Evaluate new technologies and recommend adoption (e.g., DABs, DLT, Auto Loader, Serverless Compute, event hubs) Tasks * Python, PySpark, Spark SQL, SQL Server * Azure (ADF, ADLS Gen2, Key Vault, Azure Monitor) * Databricks (Delta Lake, Unity Catalog, Workflows) * Apache Airflow * Git / Azure DevOps * Deep Spark internals (DAG optimization, spill analysis, skew handling) * Delta Lake advanced features (time travel, deletion vectors, predictive I/O) * a root Catalog governance (row/column security, external locations, system tables) * IaC - Terraform, Azure ARM templates * Bachelor’s degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience * Limited immigration sponsorship may be available * Ability to travel 10%, on average, based on work and clients served Key requirements *