Senior AI Data Architect
HumanaSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Technology, Data AnalyticsIndustries
Requirements
- Expert proficiency in SQL and Python with the ability to solve complex data logic and optimization problems
- Strong foundation in machine learning, statistics, and applied mathematics
- Demonstrated experience working on AI initiatives and data products
- Working knowledge of major cloud platforms (AWS, GCP, or Azure)
- Experience architecting end-to-end data solutions and working directly with clients or business stakeholders
- Ability to work independently with full ownership and accountability
- Proven track record of navigating ambiguity with a proactive, problem-solving mindset
- Experience leading or collaborating with diverse technical teams
- Previous experience in a data- or ML-focused company or project (required)
Responsibilities
- Lead the design, development, and deployment of scalable analytics solutions and data models
- Proactively navigate ambiguity by breaking down problems, proposing structured solution options, and driving clarity with stakeholders
- Formulate, compare, and present multiple technical approaches, guiding clients and internal teams toward the best path forward
- Architect and build high-quality data pipelines and analytics layers that support insights, reporting, and machine learning use cases
- Collaborate directly with clients to understand challenges, translate them into actionable technical requirements, and communicate progress effectively
- Lead, mentor, and collaborate with cross-functional team members including DAs, DEs, ML Engineers, and FE/BE developers
- Contribute to the development of internal data products, accelerators, and AI-powered solutions
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What are the key skills required for the Senior Analytics Engineer role?
Expert proficiency in SQL and Python is required, along with a strong foundation in machine learning, statistics, and applied mathematics. Additional requirements include demonstrated experience with AI initiatives and data products, working knowledge of major cloud platforms like AWS, GCP, or Azure, and experience architecting end-to-end data solutions.
Is this a remote position or does it require office work?
This information is not specified in the job description.
What is the salary or compensation for this role?
This information is not specified in the job description.
What is the company culture like at ShyftLabs?
ShyftLabs values passionate problem-solvers who thrive in ambiguous environments, take full ownership, and work collaboratively with cross-functional teams and clients. The company emphasizes turning big ideas into real outcomes and making a big impact with Fortune 500 clients.
What makes a strong candidate for this Senior Analytics Engineer position?
A strong candidate has previous experience in a data- or ML-focused company or project, a proven track record of navigating ambiguity with a proactive mindset, and the ability to lead or collaborate with diverse technical teams while owning end-to-end execution.
ShyftLabs
Data-driven decision-making solutions for organizations
About ShyftLabs
ShyftLabs helps organizations adopt a data-first approach to their decision-making processes. Their services focus on establishing systems that enable companies to make quicker and more informed decisions based on data analysis. This approach allows businesses to gain insights that can keep them ahead of their competitors. Unlike other companies that may offer generic consulting services, ShyftLabs emphasizes the importance of data in driving decisions, ensuring that organizations can leverage their data effectively to enhance their strategic planning and operational efficiency.
None, CanadaHeadquarters
2018Year Founded
VENTURE_UNKNOWNCompany Stage
Data & Analytics, ConsultingIndustries
11-50Employees
Benefits
Health Insurance
Hybrid Work Options
Professional Development Budget
Risks
Increased competition from startups offering innovative, cost-effective solutions.
Growing demand for in-house analytics teams reducing reliance on consultants.
Rapid AI advancements may outpace ShyftLabs' current technology offerings.
Differentiation
ShyftLabs specializes in data governance, warehousing, and predictive analysis services.
The firm empowers organizations with a data-first approach for decision-making.
ShyftLabs establishes processes for faster, insightful decisions to outpace competition.
Upsides
Increased demand for data governance due to stricter privacy regulations.
Growing interest in predictive analytics in retail for inventory optimization.
Rising adoption of cloud-based BI tools among SMEs for cost-effectiveness.
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