Primary Skills
- Data Analysis, SQL, Python, Exploratory Data Analysis, Data Storytelling & Insight Generation, Excel VBA, Insight Generation, Communication & Articulation: Vocal & Written
Specialization
- BI Foundation: Senior Analytics Manager
Job requirements
Analytics, AI & Data Engineering Consulting Lead
Experience
10–15 years of experience in Analytics, AI, Data Engineering and Technology Consulting, with demonstrated success leading enterprise-scale transformations across multiple industries.
Role Summary
We are looking for a highly accomplished Analytics, AI & Data Engineering Consultant who combines deep technical expertise with strong consulting and business leadership capabilities. The ideal candidate should have started their career as a hands-on software/data engineer, evolved into leading enterprise analytics and AI programs, and now be capable of engaging CXOs to shape data and AI strategies.
This role requires someone equally comfortable discussing cloud architecture with engineers, statistical models with data scientists, and business transformation with executive stakeholders.
Key Responsibilities
Client Leadership & Consulting
- Serve as the trusted advisor for senior client stakeholders including CIO, CDO, CTO, VP Engineering, and Business Leaders.
- Lead consulting engagements from discovery through implementation and value realization.
- Conduct business assessments, identify AI opportunities, and develop enterprise AI and Data roadmaps.
- Drive executive workshops, hypothesis-driven problem solving, and strategic advisory engagements.
- Translate business problems into scalable technology and analytics solutions.
- Design and oversee enterprise AI solutions across Predictive Analytics, Machine Learning, Deep Learning, GenAI, and Agentic AI.
- Lead development of forecasting, optimization, recommendation, computer vision, NLP, and anomaly detection solutions.
- Build production-grade ML pipelines with MLOps best practices.
- Guide experimentation, A/B testing, causal inference, statistical validation, and model governance.
- Drive responsible AI, explainability, bias monitoring, and model observability.
- Managed and designed scalable data architectures across cloud platforms.
- Lead implementation of modern data platforms using:
- Snowflake
- Databricks
- BigQuery
- Microsoft Fabric
- Redshift
- Build enterprise-grade ELT/ETL pipelines using Spark, PySpark, SQL, dbt, Airflow, Dataflow, Kafka, and cloud-native services.
- Drive Data Quality, Data Governance, Master Data Management, Metadata Management, and Data Catalog initiatives.
- Optimize performance, scalability, and cost of cloud data platforms.
- Design enterprise GenAI applications using LLMs.
- Architect Retrieval Augmented Generation (RAG) systems.
- Build AI Agents capable of reasoning, planning, orchestration, and tool usage.
- Develop multi-agent workflows for enterprise automation.
- Implement prompt engineering, evaluation frameworks, guardrails, and AI governance.
- Integrate vector databases, knowledge graphs, semantic search, and enterprise knowledge management.
- Define enterprise architecture standards for AI and Analytics platforms.
- Review solution architecture and engineering quality.
- Guide engineering teams on scalable design patterns.
- Drive API-first architecture and microservices-based AI deployment.
- Lead CI/CD implementation for analytics and ML platforms.
- Establish engineering best practices for reliability, security, observability, and maintainability.
- Lead cross-functional teams comprising Data Engineers, Data Scientists, ML Engineers, Architects, and BI Developers.
- Own solution delivery, governance, risk management, and stakeholder communication.
- Mentor technical teams and establish engineering excellence.
- Drive innovation initiatives, accelerators, reusable assets, and AI platforms.
- Support pre-sales activities, solution design, and proposal development.
- Lead client presentations, solution workshops, and executive demonstrations.
- Develop reusable AI accelerators and industry-specific offerings.
- Contribute to thought leadership through whitepapers, blogs, and conference presentations.
- Python
- SQL
- PySpark
- Any BI tool
- Strong engineering mindset with the ability to dive deep into technical discussions.
- Ability to transition seamlessly between architecture, coding, consulting, and executive discussions.
- Proven success managing teams of 20–100+ members across global delivery models.
- Experience leading multi-million-dollar analytics and AI transformation programs.
- Passion for mentoring and building high-performing engineering and consulting teams.
- Bachelor's degree in Computer Science, Information Technology, Electronics, Mathematics, Statistics, or a related engineering discipline from a premier engineering institution
- MBA, PGDM, or equivalent management degree from a premier business school.
AI & Advanced Analytics
Data Engineering & Modern Data Platforms
Generative AI & Agentic AI
Architecture & Engineering Leadership
Delivery Leadership
Business Development
Required Technical Skills
Programming
Leadership Expectations
The ideal candidate should demonstrate:
Desired Educational Background
Ideal Candidate Profile
The successful candidate will have begun their career as a hands-on software or data engineer, with strong experience in coding, system design, and data platform implementation. Over time, they should have progressed into leading analytics, AI, and engineering teams while developing strong consulting, client engagement, and business leadership capabilities. They should be equally adept at writing production-grade code when required, architecting enterprise-scale solutions, and influencing executive stakeholders to drive measurable business outcomes. This blend of technical depth, consulting acumen, and strategic leadership is essential for the role.
Skills Required
- 10-15 years experience in Analytics, AI, Data Engineering and Technology Consulting
- Proven success leading enterprise-scale transformations across multiple industries
- Experience engaging C-level stakeholders (CIO, CDO, CTO) and leading executive workshops
- Hands-on background as a software/data engineer with ability to write production-grade code
- Experience designing and implementing modern data platforms using Snowflake, Databricks, BigQuery, Microsoft Fabric, or Redshift
- Experience building ELT/ETL pipelines using Spark, PySpark, dbt, Airflow, Dataflow, or Kafka
- Proficiency in Python and SQL
- Experience with MLOps and production ML pipelines
- Experience managing global teams of 20-100+ and leading multi-million-dollar analytics/AI programs
- Experience with Generative AI, LLMs, RAG, vector databases, knowledge graphs, or semantic search
- Bachelor's degree in Computer Science, IT, Electronics, Mathematics, Statistics, or related engineering discipline
- MBA, PGDM, or equivalent management degree
Brillio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Brillio and has not been reviewed or approved by Brillio.
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Healthcare Strength — Healthcare is considered comprehensive, including medical coverage for employees and dependents alongside life, disability, and accidental death protections. Feedback suggests these protections are a core strength of the package.
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Leave & Time Off Breadth — Time-off options include paid leave and parental leave, with flexible or ‘flexible PTO’ approaches cited in some contexts. Feedback suggests this breadth helps support work-life balance when team norms permit usage.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings span counseling, financial-management sessions, fitness programs, and travel insurance, plus region-specific extras like discounted IT hardware and work-from-home essentials. Feedback suggests these add-ons enhance perceived value beyond core insurance.
Brillio Insights
What We Do
Brillio is the leader in global digital business transformation, applying technology with a human touch. We help businesses define internal and external transformation objectives, and translate those objectives into actionable market strategies using proprietary technologies. With 2600+ experts and 13 offices worldwide, Brillio is the ideal partner for enterprises that want to quickly increase their core business productivity, and achieve a competitive edge, with the latest digital solutions.
