Senior Technical Consultant, Data

• Lead the design and hands-on delivery of complex data, analytics, AI, cloud, and modern data platform solutions
• Own significant technical workstreams and solution components from discovery and design through build, test, deployment, and stabilization
• Translate business and technical requirements into scalable, secure, maintainable, and production-ready implementations
• Design, build, operationalize, secure, monitor, and optimize modern data solutions, including ingestion, transformation, orchestration, curated data layers, integrations, APIs, semantic artifacts, and data products
• Develop automated pipelines for structured and unstructured data using batch, streaming, and cloud-native patterns
• Modernize legacy SQL, ETL/ELT, data warehouse, data lake, integration, and orchestration workloads
• Apply source control, code review, CI/CD, automated testing, monitoring, observability, performance optimization, and production-readiness practices
• Lead technical testing and validation, including unit, integration, system, data-quality, regression, KPI reconciliation, defect resolution, and UAT support
• Incorporate governance and security requirements, including metadata, lineage, classification, access controls, data quality, retention/lifecycle, and catalog or semantic artifacts
• Troubleshoot complex technical and data issues, identify root causes, and drive resolution
• Estimate and plan technical work, manage dependencies and commitments, and surface risks with recommended actions
• Produce and review client-ready technical documentation, including designs, mappings, configurations, test evidence, runbooks, decisions, deployment materials, and handoff documentation
• Provide technical direction, peer review, coaching, and mentoring to technical consultants and engineers
• Partner with Principal Technical Consultants, Solution Architects, project managers, governance resources, and client SMEs
• Contribute to technical discovery, assessments, estimates, solution approaches, proofs of concept, proposals, statements of work, and pre-sales activities
• Contribute reusable engineering assets, implementation patterns, standards, lessons learned, technical enablement, onboarding, interviewing, and certification development
• Maintain expertise across modern data platforms, cloud technologies, AI, governance, analytics, integration, and emerging engineering practices

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, Data Science, or a related technical discipline, or equivalent professional experience
• Typically 8–12+ years of professional technical experience delivering enterprise data, analytics, AI, cloud, or digital transformation solutions
• Demonstrated consulting or professional services experience working directly with clients and independently owning complex technical workstreams or solution components
• Strong hands-on experience in modern data engineering and architecture, including data modeling, SQL, Python or similar programming, ETL/ELT, orchestration, data integration, APIs, data warehouse/lake/lakehouse patterns, and cloud-native services
• Experience with one or more modern data platforms such as Snowflake, Databricks, Microsoft Fabric, or comparable cloud data technologies
• Experience working in AWS, Azure, or Google Cloud environments
• Experience designing and implementing automated data pipelines for structured and/or unstructured data using batch, streaming, or event-driven patterns
• Strong understanding of software/data engineering lifecycle practices including Git/source control, peer review, CI/CD, automated testing, monitoring/observability, security, and production operations
• Ability to analyze complex source data and systems, troubleshoot root causes, validate and reconcile outputs, and communicate technical findings and recommendations clearly
• Strong client-facing communication, facilitation, documentation, analytical problem-solving, and stakeholder collaboration skills
• Demonstrated ability to guide other engineers, review technical work, and improve team quality without serving as the overall architectural authority for the engagement
• Professional certifications in Snowflake, Databricks, Microsoft Fabric, Azure, AWS, Google Cloud Platform, data engineering, AI, governance, or related enterprise technologies preferred
• Experience with metadata/catalog, lineage, data governance, semantic modeling, data quality, AI/ML, unstructured-data solutions, or search/AI integration preferred
• Experience modernizing legacy data platforms, SQL/ETL workloads, integrations, or enterprise data warehouses into cloud-native architectures preferred
• Experience contributing to technical discovery, estimates, proposals, statements of work, reference architectures, reusable engineering frameworks, or technical practice enablement preferred

• Comprehensive health insurance coverage for employees, with options to extend coverage to dependents
• Paid time off and company holidays, along with additional leave benefits as per policy
• Flexible work arrangements, supporting work-life balance
• Learning and development opportunities to support continuous growth and upskilling
• Employee wellness initiatives and programs focused on physical and mental well-being
• Retirement and statutory benefits in line with India regulations
• Inclusive and people-first culture, with a strong focus on collaboration and ownership
• Cross department training and development
• Sponsoring certifications and credentials for continued learning
• Multi-million-dollar technology lab