Senior Data Engineer
As an experienced Senior Data Engineer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. Consider an opportunity with Deloitte under our Project Delivery Talent Model (PDM) - a talent model tailored specifically for long-term, onsite client service delivery.
Responsibilities
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and/or technical teams, including escalating matters that require additional attention
- Design, develop and optimize ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks
- Write and tune PySpark/Spark SQL notebooks for large-scale data transformation
- Architect end-to-end data solutions across dev → UAT → prod environments using Unity Catalog
- Lead and drive design discussions with client architects and other counterparts
- Collaborate with different teams on data contracts and schema agreements
- Lead design and optimization of high-volume data pipeline
- Define and enforce data engineering standards - naming conventions, partitioning strategies, cluster configurations, Spark tuning
- Drive performance optimization - AQE tuning, liquid clustering, broadcast joins, shuffle partition management
- Design Databricks cluster policies, autoscaling configurations, and cost optimization strategies
- Conduct root cause analysis on production incidents and implement permanent fixes
- Mentor junior and mid-level engineers through code reviews and pair programming
- Evaluate new technologies and recommend adoption (e.g., DABs, DLT, Auto Loader, Serverless Compute, event hubs)
About the Team
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions transform mission-critical operations and enable clients to stay ahead with the latest advancements by modernizing technology and data platforms.
Requirements
- 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 requirements
Pay
The wage range for this role is $95,000 to $150,000, taking into account various factors including skill sets, experience, training, and other business needs.
Benefits
This position is aligned with the Project Delivery Talent Model benefits package. View the associated benefit package details.