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# Senior Data Engineer

- **Company:** Deloitte T.T.L.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Microsoft Azure, Code Review, Information Engineering, Extract Transform Load (ETL), Data Systems, Apache Hive, Python (Programming Language), Microsoft SQL Server, Pair Programming, Azure Data Lake, Azure Service Bus, Azure Data Factory, Cloud Monitoring, Apache Spark, Git, Data Lakes, Pyspark, Terraform, Data Pipelines, Serverless Computing, Key Vault, Databricks
- **Published:** August 10, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/senior-data-engineer-austin-tx-usa-58886148

## About the Role

* pipeline design and optimization * Define data engineering standards and tuning (AQE, partitioning, joins) * Configure Databricks clusters, autoscaling, and cost optimization * Perform root cause analysis on production incidents and implement durable fixes * Mentor junior/mid-level engineers via code reviews and pair programming * Evaluate new technologies and recommend adoption (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 or equivalent experience * Ability to travel 10% Key requirements *

## Description

Experteer Overview In this Senior Data Engineer role, you will shape and deliver end-to-end data solutions for client engagements within Deloitte's Project Delivery Model. You'll collaborate with engagement managers and cross-functional teams to design scalable data pipelines and governance. Expect to tackle large-scale transformations, optimize performance, and mentor junior engineers as you drive data platform modernization for complex environments. This opportunity lets you impact real-world outcomes while working in a collaborative, innovation-focused culture. Compensation / Benefits * Design, develop and optimize ETL/ELT pipelines with 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 using Unity Catalog * Lead design discussions with client architects and cross-functional partners * Collaborate on data contracts and schema governance * Drive high-volume data pipeline design and optimization * Define data engineering standards and tuning (AQE, partitioning, joins) * Configure Databricks clusters, autoscaling, and cost optimization * Perform root cause analysis on production incidents and implement durable fixes * Mentor junior/mid-level engineers via code reviews and pair programming * Evaluate new technologies and recommend adoption (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 or equivalent experience * Ability to travel 10% Key requirements *


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