Senior Data Engineer

Experteer Overview As a Senior Data Engineer at Deloitte, you will design and optimize large-scale data pipelines and end-to-end data solutions within a collaborative, client-focused environment. You will work with cross-functional teams to shape data architectures and governance, leveraging cloud data platforms to deliver impactful insights. The role combines hands-on engineering with leadership in design discussions, mentoring, and technology evaluation, offering opportunities to influence client outcomes and modernize data platforms. Compensation / Benefits * Communicate with Engagement Managers and project teams, escalating issues when 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, partitioning, cluster configs, Spark tuning) * Drive performance optimization (AQE tuning, liquid clustering, broadcast joins, shuffle partition management) * Design Databricks cluster policies, autoscaling, and cost optimization * Conduct root-cause analysis on production incidents and implement fixes * Mentor junior and mid-level engineers via code reviews and pairing * 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 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 Key requirements *

when 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, and cost optimization * Conduct root-cause analysis on production incidents and implement fixes * Mentor junior and mid-level engineers via code reviews and pairing * 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 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 Key requirements *