Requirements

Key Responsibilities

Onboarding Delivery & Workstream Ownership

• Own named workstreams within enterprise onboardings (source connections, historical ingestion, normalization specs, QA) under a Director, or own end-to-end onboarding for lower-complexity clients from kickoff through dashboard-ready output
• Build and maintain a shared delivery plan for your workstreams — dependencies, owners, dates, blockers — and drive them to committed go-live dates while running several concurrent onboardings without dropping threads
• Surface scope, data-quality, and timeline risk early, with a recommendation attached rather than just a flag

Data Requirements Consultancy & Model Readiness

• Act as the client's consultant on preparing data to meet Measured's model requirements — advising on structure, granularity, historical depth, and field-level detail so gaps are designed out rather than discovered at QA
• Distinguish firm requirements from acceptable tradeoffs, make and defend those calls in the moment with a clear account of what's gained and given up, and push back on requests that would compromise model integrity by offering a workable alternative
• Judge whether a client data limitation is a genuine blocker or manageable caveat and set expectations before go-live; escalate precedent-setting tradeoffs to your Director with a recommendation

Data Source Connection & Historical Ingestion

• Scope each client's required feeds (media/vendor cost, transaction/source-of-truth, organic, custom), determine the right ingestion method, and stand up connections across APIs, file-based feeds, warehouse shares, and direct integrations
• Land the full history each feed requires — not just go-forward — and prove completeness against the client's own reporting
• Diagnose ingestion failures (auth, schema drift, partial files, delivery gaps, silent upstream changes), partner with client-side engineers and vendors to resolve them, and establish monitoring so feeds stay healthy post-go-live

Data Normalization & Specification

• Author and maintain the specification layers mapping raw client data into Measured's normalized model, translating inconsistent naming and taxonomy into structured, rules-driven mappings
• Assess every spec change for downstream impact before it goes live, and balance client-specific accuracy against patterns reusable across the book of business
• Document mapping logic and the reasoning behind judgment calls so the next person can maintain it

QA & Output Validation

• Own QA for your workstreams — the data isn't done until it ties out against client source-of-truth, vendor exports, and upstream feed tables
• Write advanced SQL to validate transformations, surface anomalies, quantify variance, and isolate root cause
• Define and document acceptance criteria, and sign off with a written statement of coverage, known gaps, and caveats

Client Partnership & Communication

• Serve as a credible, trusted technical presence for client stakeholders across marketing, analytics, and data engineering, representing Measured with polish in front of enterprise stakeholders, including in difficult conversations
• Independently lead client-facing working sessions (discovery, spec reviews, QA walkthroughs, go-live readiness), translating technical requirements into terms marketers can act on and vice versa
• Manage client expectations on timelines and dependencies with transparency, and gather/synthesize client feedback to inform product and onboarding improvements

Subject Matter Expertise & Technical Depth

• Develop deep expertise in Measured's data pipelines, normalization layers, and platform architecture, and become the go-to expert on specific feed types, vendor integrations, or client verticals
• Understand incrementality testing and media mix modeling well enough to know why the data has to be shaped the way it is, maintaining a working command of what each Measured product requires from the data — and the reasoning behind it — so client guidance is grounded in the model rather than convention
• Stay current on product roadmap and platform changes that affect how client data must be prepared, partnering with Product and Engineering to translate technical architecture into client-facing guidance
• Serve as the internal reference point when data-requirements questions arrive from Sales, Solutions, and Customer Success
• Contribute to technical documentation, implementation runbooks, and internal training materials, and represent the implementation perspective in cross-functional initiatives and product development discussions

Knowledge Management, Documentation & Peer Enablement

• Create and maintain implementation runbooks, spec-writing standards, onboarding playbooks, and process documentation
• Document recurring data issues with root cause analysis and prevention strategies
• Share hard-won client and feed knowledge so no onboarding depends on one person's memory
• Serve as a second pair of eyes for peers on complex specs and QA logic
• Ensure documentation stays current with product and pipeline changes
• Model excellence in client communication, technical depth, and operational discipline

Process Improvement & Repeatability

• Streamline onboarding by automating manual, repeated, or error-prone steps, and build reusable templates, spec patterns, and validation queries that shorten time-to-value for future clients.
• Improve quality and scalability by catching requirements gaps at discovery rather than QA, surfacing cross-client issues as product/pipeline asks, and partnering with your Director and VP, Technical Implementations, on strategic initiatives like data health monitoring, proactive alerting, QA frameworks, and applying agentic AI approaches across operations.

Cross-Functional Collaboration

• Partner with Customer Success on onboarding status, launch readiness, and client health; support Sales and Solutions during technical scoping and pre-sales data-feasibility discussions
• Work with Engineering and Data Science on pipeline changes, ingestion defects, and model-readiness of client data, and with Product to communicate client pain points, feature requests, and usability feedback
• File and shepherd well-specified internal requests — with sample rows and expected behavior — so downstream teams can act without a follow-up round, and contribute to cross-functional projects that improve onboarding experience and platform reliability

Ideal Experience

Required Experience

• 5+ years of experience in technical implementation, data onboarding, solutions consulting, or technical account management in B2B SaaS, ideally with enterprise clients
• 3+ years in a directly client-facing role owning technical delivery with external stakeholders
• Extensive client-facing experience - comfortable leading working sessions, spec reviews, and candid timeline conversations with enterprise stakeholders, and equally comfortable doing the hands-on data work yourself
• Consultative judgment with data requirements - demonstrated experience advising clients on how to prepare data for a specific analytical or modeling purpose, including telling a client no and putting a workable alternative in front of them
• Strong technical proficiency in data platforms, SQL, APIs, and integrations with hands-on build and troubleshooting experience
• Experience with marketing technology platforms including advertising platforms (Facebook, Google, TikTok) and analytics tools (GA4, Adobe Analytics)
• Proven ability to diagnose and resolve complex data issues including data pipeline problems, integration errors, schema mismatches, and incomplete historical loads
• Experience owning delivery of complex, multi-stakeholder projects against committed timelines
• Experience guiding peers or client teams through technical processes they don't own
• Working proficiency with project and issue tracking (Jira, Asana, or similar) to run multi-workstream delivery
• Track record of driving process improvements that measurably improve team efficiency or delivery speed
• Excellent written and verbal communication skills with ability to explain technical concepts to diverse audiences
• Client-first mindset with proven ability to build trusted relationships with technical and non-technical stakeholders alike
• BA/BS preferred; background in technical field, data analytics, or related discipline

Technical Skills

• Advanced SQL proficiency for querying, validating transformations, reconciling loaded output against source, and diagnosing data quality issues, plus the ability to read technical logs, error messages, and pipeline diagnostics
• Strong understanding of ETL/ELT pipelines, data warehouses, and integration patterns, including cloud data platforms (Snowflake, BigQuery, Databricks, Redshift) and familiarity with orchestration tooling (Airflow or similar) a plus
• Experience with APIs and integrations (authentication, rate limits, error handling) and file-based data delivery (S3, SFTP, cloud storage), including file spec design, schema definition, and delivery troubleshooting
• Practical skill in data mapping and normalization — building rules-driven logic that turns inconsistent client taxonomies into a clean model — and experience reconciling transaction/source-of-truth data to a client's own reported numbers
• Knowledge of marketing analytics concepts including attribution, incrementality, and media mix modeling; familiarity with data visualization tools (Tableau, Looker, Mode) and scripting/analysis tools (Python, R) a plus; understanding of data privacy regulations (GDPR, CCPA); and comfort running several onboardings or workstreams concurrently, each at a different phase

Ownership & Influence Skills

• Proven ability to drive delivery through people you don't manage - client teams, vendors, and internal partners
• Strong facilitation instincts - keeps a working session on track and ends it with decisions and owners
• Knowledge-sharing mindset that elevates team capabilities through documentation and training
• Comfortable pushing back - on a client's assumption, an unrealistic date, or a spec that won't hold up - and can name the model-level reason why
• Leads by example, modeling excellent client communication, technical rigor, and operational discipline
• Collaborative working style that inspires confidence and builds trust on both sides of the engagement

Key Attributes

• Technical Expert: Deep curiosity about how systems work with commitment to continuous technical learning
• Client Champion: Passionate about delivering exceptional experiences and building client trust
• Strategic Thinker: Sees beyond the single feed to identify patterns, systemic issues, and reusable solutions
• Sound Judgment: Knows the difference between a requirement that cannot bend and one that can, and can explain which is which to a client without hedging
• Clear Communicator: Translates technical complexity into clarity for clients and team members alike
• Ownership Mindset: Takes full accountability for delivery, quality, and the commitments made to the client. Drives work to a verified, signed-off end state rather than a mostly-working one
• Calm Under Pressure: Maintains composure and clarity during compressed timelines, shifting client requirements, and high-visibility launches
• Growth-Oriented: Proactively identifies and drives improvements to processes, documentation, and team capabilities. Receptive to feedback and committed to continuous improvement
• Leads with integrity and embraces diversity in all forms

Benefits

• 100% Remote
• Competitive Total Rewards and flexible paid time off
• Opportunities to give back through Measured for Good
• Engaged, diverse, and curious culture
• Award-winning technology powered by an agile, collaborative team

Originally posted on Himalayas