databricks engineer - Delivery Senior Consultant, Data Engineering and Conversion Solutions

Deloitte T.T.L.
Lake Mary, FL, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Transformation Data Warehousing Digital Assets Python (Programming Language) Metadata SQL Databases
+6 more
Systems Integration Cloud Platform System Pyspark Data Management Data Pipelines Databricks

Job description

Job Title: databricks engineer - Delivery Senior Consultant, Data Engineering and Conversion Solutions, databricks engineer - Delivery Senior Consultant, Data Engineering and Conversion Solutions Our Deloitte AI & Engineering team to transform technology platforms, drive innovation, and help make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

As a databricks engineer, you will help design, build, and support data management solutions that enable reliable, scalable, and secure use of data across business and technology functions. In this role, you will collaborate with cross-functional stakeholders to develop data pipelines, improve data quality, and support data governance and integration efforts. The ideal candidate brings hands-on experience in data engineering and the ability to manage multiple priorities in a dynamic environment.

Work you’ll do

As a US Delivery Center Senior Consultant, Data Engineering and Conversion Solutions on the team, you will:

  • Design, build, test, and maintain data pipelines and data integration solutions
  • Support data modeling, transformation, and storage processes across structured and unstructured data sources
  • Monitor data workflows, troubleshoot issues, and implement fixes to improve reliability and performance
  • Collaborate with business, analytics, and technology teams to define data requirements and support delivery priorities
  • Apply data quality, metadata, and governance standards across data assets and processes

Requirements

  • 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, Required:

  • Bachelor’s degree required
  • Must be able to obtain and maintain the required clearance for this role
  • 2+ years of experience in data engineering, data integration, or data management, including 2+ years of experience with Structured Query Language (SQL)
  • 2+ years of experience building or supporting extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines
  • 2+ years of experience with Python and PySpark
  • 1+ years of experience with Databricks and cloud-based data platforms, including data pipeline development and data transformation
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Preferred:

  • Experience with data warehousing concepts and dimensional data modeling
  • Experience with data quality, metadata, or data governance processes
  • Experience working with application programming interfaces (APIs) and system integrations
  • Experience supporting Agile delivery teams
  • Experience in a professional services environment
  • Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations
  • Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location

About the company

Deloitte’s Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte’s scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

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