Senior Data Engineer

Experteer Overview As a Senior Data Engineer, you will design and optimize data pipelines and data platforms for complex client environments. You’ll work with cross-functional teams to deliver end-to-end data solutions, influence architectural decisions, and mentor junior engineers. This role emphasizes hands-on data engineering, performance tuning, and governance in Azure and Databricks ecosystems. You’ll collaborate with client architects to drive scalable, cost-aware data solutions while advancing Deloitte’s AI & Engineering initiatives. Compensation / Benefits * Design, develop and optimize ETL/ELT pipelines using Azure Data Factory and Databricks * Write and tune PySpark / Spark SQL notebooks for large-scale data transformation * 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, partitioning, cluster configs, Spark tuning) * Drive performance optimization (AQE tuning, liquid clustering, broadcast joins, shuffle partition management) * Design Databricks cluster policies, autoscaling, 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 in related IT discipline; or equivalent experience * Limited immigration sponsorship may be available * Ability to travel 10% on average Key requirements *

tune * Define and enforce data engineering standards (naming, partitioning, cluster configs, Spark tuning) * Drive performance optimization (AQE tuning, liquid clustering, broadcast joins, shuffle partition management) * Design Databricks cluster policies, autoscaling, 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 - aaaaa Unity Azure ARM templates * Bachelor’s degree in related IT discipline; or equivalent experience * Limited immigration sponsorship may be available * Ability to travel 10% on average Key requirements *