Deloitte

Databricks Data Engineer II

Deloitte$86K — $170K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
  • 3+ years of experience in data engineering or ETL development
  • 2+ years of experience with data pipelines in Databricks (Apache Spark, Python, SQL)
  • Experience implementing data models and cloud-based processing workflows
  • Experience with at least one cloud platform (AWS, Azure, or GCP)
  • Ability to travel 50% based on client needs
  • Limited immigration sponsorship may be available.

Responsibilities

  • Design, build, and maintain data engineering solutions using Databricks and Apache Spark.
  • Support modernization of data platforms with cloud-based data ingestion and transformation.
  • Develop batch and streaming data workflows for analytics and AI.
  • Apply best practices for data architecture and modeling to enhance data quality.
  • Collaborate with teams to troubleshoot issues and support large-scale transformation projects.

Benefits

  • Collaborative work environment with opportunities for professional relationships and project leadership.
  • Exposure to cutting-edge technologies in the field of AI and data.
  • Opportunity to work with a diverse range of clients on large-scale data projects.
  • Focus on continuous learning and skill development in a fast-paced industry.
Full Job Description
Work you'll do

As a Databricks Data Engineer on the Core AI & Data team, you will be responsible for:
  • Design, build, and maintain data pipelines and data engineering solutions using Databricks, Apache Spark, Python, and Structured Query Language (SQL)
  • Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns
  • Develop and maintain batch and streaming data workflows that support reporting, analytics, and artificial intelligence use cases
  • Apply data architecture, integration, and data modeling practices to improve data quality, scalability, and platform performance
  • Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs
A successful candidate would possess these skills:
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
The team

Deloitte's Core AI & Data practice helps organizations modernize data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence capabilities across the business. The team works with clients to architect, engineer, and deploy cloud-based data solutions that improve decision-making, enable innovation, and support large-scale transformation. Practitioners collaborate across business and technology functions to solve complex challenges in data modernization, governance, platform engineering, and insight delivery.

Qualifications Required:
  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
  • 3+ years of experience in data engineering, extract, transform, load (ETL) development, or data platform engineering
  • 2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and Structured Query Language (SQL)
  • Experience implementing data models, data integration patterns, and cloud-based data processing workflows
  • Experience working with at least one cloud platform: Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.
Preferred:
  • Experience with Delta Lake, Databricks Workflows, and Unity Catalog
  • Experience using Git-based version control and continuous integration/continuous deployment pipelines
  • Experience supporting batch and streaming data workloads
  • Experience with data warehousing, lakehouse architecture, and performance optimization
  • Experience supporting analytics or machine learning data pipelines
  • Experience working in consulting or client service delivery environments
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 to $170,900.

About Deloitte

Deloitte is a multinational professional services network that provides audit, tax, consulting, enterprise risk and financial advisory services. The company was founded in London in 1845 and has since grown to become one of the largest professional services firms in the world. Deloitte has over 330,000 employees in more than 150 countries and territories. The company's mission is to help clients achieve their goals and make an impact that matters in their businesses and communities.
Learn more about Deloitte
Size
330,000 employees
Industry
Founded
1999

Similar Jobs

More Jobs at Deloitte

More Information Technology Jobs

Find similar Databricks Data Engineer II jobs: