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Job Location: Detroit, MI
The SFL Scientific, a Deloitte Business practice brings together several key capabilities to architect integrated programs that transform our clients’ businesses, including Strategic Growth Transformation, Transformation Strategy & Design, Technology Strategy & Business Transformation, and AI & Data Strategy.
Professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices about where to play and how to win – ultimately driving growth and enterprise value.
We are hiring a Senior Data Engineer to support the design and develop solutions for various organizations looking to implement tools, software, and processes that support machine learning and AI initiatives across healthcare, life sciences, manufacturing, energy, and other sectors.
Work you’ll do
As a Senior Data Engineer you work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate expertise in cloud deployment, DevOps, MLOps, data engineering, and streamlining IT infrastructure processes for organizations across a wide variety of industries.
In our consultative approach, we are platform agnostic and are committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies across cloud, HPC, DevOps, and MLOps to create solutions and products that address complex issues and business problems faced by global organizations to include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Join us to expand your technical career through the lens of consulting and work on many novel projects and use cases to expand your data science & AI skills.
- Work with clients to design, develop, and deploy new architectures for machine learning & automation applications such as ELT functions, HPC/compute infrastructure, AWS/Azure solutions, database solutions, and optimization of DevOps procedures
- Leverage skills in modern data architecture, cloud engineering, data transformation, and management of structured and unstructured data sources
- Support and enhance data architecture, and data pipelines, and define database schemas (Graph DB, SQL, NoSQL) to support algorithm scalability and deployment based on agile business priorities and technology initiatives
- Participate in architectural discussions to ensure solutions are designed for successful deployment, security, and high availability in the cloud or on-prem
- Adopt and maintain best engineering practices in automation, HPC, CI/CD, and AIOps
The Team
SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Basic Qualifications:
- Bachelor’s degree in a STEM field or equivalent experience (Computer Science, Engineering, Physics etc.); Master’s degree preferred
- 4+ years’ experience in data engineering, cloud engineering, MLOps, while building highly scalable and secure solutions
- Proficient in Python, SQL, Shell scripting
- Experience with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g. AWS, Azure), containerization, and supporting analytics libraries
- Expertise with code management and DevOps tools (e.g., Docker, Kubernetes, Jenkins, etc.)
- Experience with workflow and data management solutions such as Airflow, Kafka, Glue, etc.
- Experience designing data architectures and understanding of different types of databases or platforms (relational, NoSQL, graph, etc.)
- Strong analytical and problem-solving skills with the ability to develop novel and efficient solutions
- Limited immigration sponsorship may be available
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
- Live within commuting distance to one of Deloitte’s consulting offices
Preferred Qualifications:
- Master’s or Ph.D. degree in Computer Science, Information Technology, or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect).
- Expertise in designing and scaling IT architectures, data lakes, & database schemas (Graph, SQL, NoSQL), etc.
- Demonstrated experience launching AI/ML solutions into production environments, such as into cloud or HPC/GPU environments
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