Blend360

Analytics Engineer

• Implement the curated data model layer in dbt across 18 data domains, working closely with the Onshore Analytics Engineering Lead.
• Design and build dbt models across the full layered architecture: staging, intermediate, and mart layers.
• Implement comprehensive dbt testing strategies, including unique, not_null, accepted_values, relationships, and custom tests to ensure data quality and reliability.
• Develop and optimize incremental models to handle high-volume domains processing billions of events efficiently.
• Generate and maintain thorough project documentation, including column descriptions and lineage graphs, to support transparency and team collaboration.

QA Engineer

• Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains.
• Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps.
• Execute structured acceptance testing for each pipeline prior to promotion to production environments.
• Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives.
• Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance.
• Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve.

Data QA Analyst

Marketing

• Act as the operational driver for a complex, multi-channel marketing campaign.
• Translate high-level plans into executable workstreams.
• Manage end-to-end execution across marketing workstreams.
• Serve as the central point of coordination across teams.
• Provide regular updates on campaign status, timelines, and risks.

Senior Marketing Manager, Campaign Execution

Full-stack Engineer

• Own architecture and delivery across multiple workstreams for Intelligent Applications.
• Define 'how we build' for forward deployed engagements—templates, standards, quality gates.
• Mentor and guide multiple engineers.
• Bring observability/security to the forefront and operationalize LLM/agent delivery into repeatable, safe workflows (evals, guardrails, monitoring, human-in-the-loop where needed).
• Lead multiple streams (UI/API/data) with clear sequencing, risks, and integration plans.
• Define reference architectures and standards: SOLID/MVC boundaries, error handling, testing, observability, security.
• Drive performance and data architecture decisions: SQL/query patterns, indexing strategy, data contracts.
• Create reusable accelerators: scaffolds, templates, spec/context packages, PR checklists, CI quality gates—including LLM/RAG reference modules and evaluation scaffolding.
• Partner with data teams when engagements lean on Databricks or Snowflake for analytics/ML adjacency (contracts, identity, performance patterns).
• Operationalize CI/CD and containerization standards: pipeline guardrails, environment parity, container-first dev workflows, and release verification patterns.
• Coach senior + mid-level engineers; improve team throughput and quality.
• Partner with leadership and clients to quantify impact and adoption.

Lead Full Stack Engineer

Solutions Engineer

• Own the practice of Solutions Architecture across a portfolio of engagements: talent, methods, risk posture, and technical strategy aligned to business outcomes—especially as clients adopt Intelligent Applications and LLM platforms.
• Set what “good solutioning” looks like—review models, accelerators, risk frameworks—and represent architecture tradeoffs to executive stakeholders.
• Contribute to highest-risk programs directly, primary accountability is scaling the capability.
• Set practice strategy: capability model, hiring bar, leveling alignment, onboarding, communities of practice.
• Establish portfolio governance: architecture review boards, exceptions, security/reliability minimums, vendor/architecture risk processes.
• Grow talent: performance coaching, sponsorship, succession planning for Staff/Principal paths.
• Define reusable assets: reference architectures, decision templates, NFR catalogs, threat modeling kits, engagement playbooks.
• Partner with sales/delivery leadership on technical win strategy, estimates risk ranges, and delivery feasibility.
• Drive LLM architecture governance with measurable controls: policy, evaluations, monitoring, incident readiness, vendor/model posture.
• Align CI/CD, observability, and platform standards across engagements with enterprise constraints.

Solutions Architect

Project Manager

• Project Management & Operational Execution Lead end-to-end project management for tactical marketing initiatives, campaign executions, and smaller portfolio-level projects.
• Build and manage project timelines, workback schedules, dependencies, approvals, and milestone tracking to ensure on-time delivery.
• Manage multiple concurrent workstreams while balancing shifting priorities and business needs.
• Identify execution risks, escalate blockers proactively, and drive issue resolution to maintain delivery quality and speed.
• Marketing Workflow & Process Management Utilize workflow and asset management tools (such as Aprimo or similar platforms) to manage project intake, routing, approvals, and asset submissions.
• Ensure adherence to established governance, campaign workflows, and operational standards.
• Maintain project documentation, trackers, meeting notes, and status updates to ensure stakeholder visibility and accountability.
• Cross-Functional Coordination Partner with internal marketing stakeholders, creative teams, agency partners, and external vendors to coordinate deliverables and approvals.
• Facilitate clear handoffs between business, creative, legal, compliance, and production teams.
• Support portfolio-level messaging initiatives and campaign execution efforts across multiple business priorities.
• Creative & Messaging Support Contribute to messaging refinement, creative execution planning, and campaign readiness for select initiatives.
• Support adaptation of campaign assets and messaging across channels while ensuring consistency with brand and compliance requirements.
• Help pilot and improve operational processes related to campaign delivery and creative production.
• Stakeholder Communication Provide regular status updates, timeline communication, and issue tracking across stakeholders.
• Manage expectations and ensure alignment in a matrixed, cross-functional environment. Support leadership reporting and operational reviews as needed.

Marketing Project Manager, Financial Services

Vice President

• Own senior-most consulting relationships with C-Suite executives (CEO, CFO, COO, CAIO, CTO) at Fortune 1000 and PE-portfolio clients across transformation engagements.
• Serve as Blend360's trusted strategic advisor to client leadership—guiding them through the business case, organizational implications, and risk landscape of agentic adoption.
• Lead executive steering committees, board-level briefings, and transformation governance forums on behalf of our clients.
• Cultivate deep, multi-year relationships that expand Blend360's footprint within accounts and generate new opportunities through referral and reputation.
• Lead the design and facilitation of Agentic Transformation roadmaps—defining the sequencing, business value, and organizational change required to move clients from current state to agentic maturity.
• Frame transformation in terms of business outcomes: cost efficiency, revenue growth, competitive differentiation, risk reduction—not technology outputs.
• Assess and guide organizational readiness for agentic transformation—spanning culture, workforce, governance, operating model, and change capacity.
• Help clients design the structures, roles, and accountability models needed to sustain agentic operating models beyond initial implementation.
• Translate technical complexity into clear, resonant narratives for non-technical executives and boards.

SVP, Agentic Transformation

• Serve as a central driver of execution and governance across a portfolio of strategic marketing initiatives
• Partner closely with marketing leaders, strategy teams, and cross-functional stakeholders to ensure programs are delivered on time, within scope, and aligned to business objectives
• Establish and maintain program governance frameworks, including project charters, RACI matrices, decision logs, and escalation protocols
• Drive accountability across stakeholders without direct authority
• Develop and manage integrated marketing roadmaps, including timelines, milestones, dependencies, and deliverables
• Track progress against strategic priorities to ensure on-time, on-budget delivery
• Identify risks, issues, and blockers, and proactively implement mitigation strategies
• Partner with marketing managers, strategy leads, and execution teams to ensure seamless delivery across initiatives
• Lead day-to-day program management activities, including scheduling and facilitating meetings, capturing action items, and tracking follow-ups
• Deliver regular status updates and executive-level reporting, including progress summaries, risks, and key decisions.

Project Manager, Wealth Management Products

Product Manager

• Manage multiple projects within a B2B portfolio
• Provide efficient and effective coordination of a complex range of activities
• Ensure effective identification of risks and pro-active solutioning
• Responsible for strategically growing a B2B portfolio
• Oversee and manage the supplier enablement process for virtual card solutions
• Collaborate with internal and external stakeholders

Commercial Card Product Manager

Data Engineer

• Lead the design and implementation of data ingestion architectures in Snowflake , ensuring scalability and reliability.
• Own the development of end-to-end ELT pipelines integrating multiple data sources.
• Design and enforce data quality frameworks , including validation rules, testing strategies, and monitoring.
• Apply and drive Medallion Architecture (Bronze, Silver, Gold) best practices across data pipelines.
• Build and optimize data pipelines and architectures on AWS (S3, Glue, Lambda, EMR, etc.).
• Develop and enhance data validation and ingestion frameworks , including UI components (Streamlit-based) when needed.
• Act as a technical leader , guiding best practices in data engineering, governance, and pipeline reliability.
• Proactively identify risks, bottlenecks, and data quality issues , and implement mitigation strategies before they impact delivery.
• Contribute to data governance initiatives , including data definitions, lineage, and stewardship practices.
• Drive documentation and continuous improvement of data platform processes.

Data Engineering Lead

Data Scientist

• Lead the technical design, development, and architecture of cutting-edge AI and Generative AI solutions.
• Serve as a trusted technical advisor to national and international clients.
• Provide hands-on technical leadership and guidance throughout the entire project lifecycle.
• Drive thought leadership in the evolving landscape of GenAI, large language models (LLMs), agentic AI systems, and emerging AI techniques.
• Actively participate in presales activities, providing deep technical expertise for proposal development.
• Collaborate with clients to understand their business challenges and translate them into actionable AI strategies and technical roadmaps.
• Lead and manage specific technical workstreams within complex projects.
• Contribute to the continuous development and technical refinement of Blend360's AI and Generative Solutions offerings.

Senior Director, AI Engineering / VP, Data Science

• Own the data science product roadmap, aligning business objectives with model development priorities
• Manage inbound requests from Sales and Customer Success teams, triaging and prioritizing based on business impact
• Translate high-level business goals into product requirements for the DS squad and engineering org
• Oversee model development lifecycle, including dataset validation, model tradeoffs, and cost considerations
• Ensure model quality and robustness before reaching production, identifying issues early in the development cycle
• Define success metrics and scope data science initiatives in collaboration with technical teams
• Drive coordination across teams with a product-first mindset, balancing delivery with strategic thinking
• Act as the central point of contact between the data science squad and the broader engineering organization