Senior Technical Consultant, Data

Expectations:

Senior Technical Consultants are expected to consistently demonstrate strong technical execution, structured thinking, consultative behavior, ownership, proactive communication, and emerging technical leadership. They should independently drive complex technical work while helping less-experienced team members succeed and maintaining alignment with the broader architecture and delivery strategy. 

Leadership and Ownership 

• Take end-to-end ownership of assigned technical workstreams and outcomes, not just individual development tasks. 

• Plan and prioritize technical work, anticipate dependencies, identify risks early, and drive routine next steps without requiring step-by-step direction. 

• Bring problems with analysis, options, and a recommended path forward; escalate early when decisions or risks exceed workstream authority. 

• Maintain accountability for the quality, completeness, timeliness, and production readiness of technical deliverables within assigned scope. 

Consulting and Client Effectiveness 

• Clearly define technical problems, impacts, assumptions, constraints, and success criteria before moving into execution. 

• Connect technical decisions to client business objectives, operational outcomes, delivery feasibility, and long-term maintainability. 

• Communicate in a structured, concise, audience-appropriate manner and participate confidently in client-facing workshops and technical decision-making. 

• Provide insights and recommendations rather than only status updates or technical findings. 

Technical Excellence 

• Demonstrate deep hands-on capability in one or more modern data, cloud, analytics, AI, governance, or integration disciplines and sufficient breadth to understand adjacent components. 

• Design and implement solutions that are scalable, secure, testable, maintainable, observable, performant, and supportable. 

• Apply architecture and engineering standards consistently and use design/code reviews to improve quality across the team. 

• Balance technical quality with delivery constraints, client priorities, implementation effort, and operational realities. 

Team Leadership and Practice Contribution 

• Provide clear technical guidance, constructive peer review, and practical coaching to less-experienced technical consultants. 

• Help teams operate with ownership, structured problem solving, engineering discipline, and proactive communication. 

• Contribute reusable assets and lessons learned that improve delivery quality, scalability, and consistency across the practice. 

• Demonstrate readiness for progression by increasingly shaping technical direction while recognizing that enterprise architecture governance and overall technical accountability sit with the Principal Technical Consultant. 

Roles and Responsibilities:

Technical Delivery and Workstream Leadership 

• Own and lead complex technical workstreams or major solution components from discovery and design through build, test, deployment, and stabilization. 

• Lead technical working sessions, design discussions, demonstrations, troubleshooting sessions, and implementation planning with client and AHEAD teams. 

• Translate business requirements, source-system knowledge, architecture direction, and acceptance criteria into practical, scalable, secure, and maintainable technical solutions. 

• 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 robust automated pipelines for structured and unstructured data using batch, streaming, and cloud-native patterns as appropriate. 

• Modernize legacy SQL, ETL/ELT, data warehouse, data lake, integration, and orchestration workloads; support dependency mapping, reverse engineering, migration, cutover, and stabilization. 

• Apply engineering discipline through source control, code review, CI/CD, automated testing, monitoring, observability, performance optimization, and production-readiness practices. 

• Lead technical testing and validation activities including unit, integration, system, data-quality, regression, KPI reconciliation, defect resolution, UAT support, and Definition of Done / acceptance criteria. 

• Incorporate governance and security requirements into technical delivery, including metadata, lineage, classification, access controls, data quality, business definitions, retention/lifecycle, and catalog or semantic artifacts. 

• Troubleshoot complex technical and data issues, identify root causes, develop options, and drive resolution with business users, client SMEs, architects, and engineering teams. 

• Estimate and plan technical work within agile delivery models, manage dependencies and technical commitments, and proactively surface risks or delivery impacts with recommended actions. 

• Produce and review client-ready technical documentation including designs, mappings, configurations, test evidence, runbooks, decisions, deployment materials, and handoff documentation. 

Technical Leadership and Team Enablement 

• Provide day-to-day technical direction to Technical Consultants, Associate Technical Consultants, and offshore/onshore engineers within assigned workstreams. 

• Review code, designs, data models, pipelines, integrations, and engineering deliverables for quality, consistency, maintainability, and alignment with established architecture and standards. 

• Coach team members on structured problem solving, engineering practices, troubleshooting, documentation, and client-ready communication. 

• Drive consistency across implementation by leveraging AHEAD reference architectures, reusable components, templates, engineering frameworks, and delivery standards rather than recreating solutions. 

• Partner closely with Principal Technical Consultants, Solution Architects, Senior Consultants, Principal Consultants, Project Managers, governance resources, and client SMEs to keep technical execution aligned with solution direction and business outcomes. 

• Act as a technical escalation point within assigned workstreams and know when issues require escalation to the Principal Technical Consultant or architecture leadership. 

Client Consulting and Solution Development 

• Operate as a consultant, not only a technical task executor: understand the client problem, business context, expected outcome, constraints, and tradeoffs before recommending or implementing a solution. 

• Communicate technical decisions, risks, assumptions, dependencies, tradeoffs, and recommendations clearly to technical and business stakeholders. 

• Build credibility with client technology and business stakeholders through preparation, sound technical judgment, reliable execution, and proactive communication. 

• Contribute to technical discovery, assessments, estimates, solution approaches, proofs of concept, proposals, statements of work, and pre-sales activities with implementation insight grounded in delivery feasibility, effort, dependencies, and risk. 

• Identify opportunities for technical improvement, modernization, automation, or follow-on work and raise them through the appropriate engagement and account leadership. 

Practice Development and Continuous Improvement 

• Contribute reusable engineering assets, implementation patterns, accelerators, standards, lessons learned, and technical documentation back to the Data Practice. 

• Support knowledge sharing, technical enablement, onboarding, interviewing, and certification development for the technical consulting community. 

• Maintain current expertise in modern data platforms, cloud technologies, AI, governance, analytics, integration, and emerging engineering practices. 

• Pursue relevant technical certifications and develop broader consulting, communication, facilitation, business, and delivery skills in preparation for Principal Technical Consultant responsibilities. 

Qualifications:

Required 

• 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, and 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 as applicable. 

• 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. 

Preferred 

• Professional certifications in Snowflake, Databricks, Microsoft Fabric, Azure, AWS, Google Cloud Platform, data engineering, AI, governance, or related enterprise technologies. 

• Experience with metadata/catalog, lineage, data governance, semantic modeling, data quality, AI/ML, unstructured-data solutions, or search/AI integration. 

• Experience modernizing legacy data platforms, SQL/ETL workloads, integrations, or enterprise data warehouses into cloud-native architectures. 

• Experience contributing to technical discovery, estimates, proposals, statements of work, reference architectures, reusable engineering frameworks, or technical practice enablement.