Sr. Technical Implementations Specialist
New
M
MeasuredMarketing Analytics
US RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in technical implementation, data onboarding, solutions consulting, or technical account management in B2B SaaS
- Required Skills
- SQLJiraRESTful APIsAsana
Requirements
- 5+ years of experience in technical implementation, data onboarding, solutions consulting, or technical account management in B2B SaaS.
- 3+ years in a directly client-facing role owning technical delivery with external stakeholders.
- Proficiency with SQL for data validation, spot-checking, and troubleshooting reporting outputs.
- Extensive experience with marketing technology platforms, advertising platforms (Meta, Google, TikTok), and analytics tools (GA4, Adobe Analytics).
- Practical understanding of data mapping, normalization, and ETL/ELT pipeline concepts.
- Experience with APIs and file-based data delivery methods such as S3 or SFTP.
- Proven ability to diagnose and resolve complex data issues including integration errors, schema mismatches, and incomplete loads.
- Experience guiding peers or client teams through technical processes.
- Proficiency with project and issue tracking tools like Jira or Asana.
- Excellent written and verbal communication skills with the ability to explain technical concepts to diverse audiences.
- BA/BS degree preferred in a technical field, data analytics, or related discipline.
Responsibilities
- Own named workstreams within enterprise onboardings including source connections, historical ingestion, normalization, and QA.
- Build and maintain shared delivery plans for concurrent onboarding workstreams to meet committed go-live dates.
- Act as a consultant to clients on preparing data to meet model requirements, advising on structure, granularity, and field-level detail.
- Scope client data feeds, determine ingestion methods, and establish connections via APIs, file-based feeds, or warehouse shares.
- Maintain specification layers that map raw client data into a normalized model using rules-driven mappings.
- Validate data outputs against client reporting and vendor exports to ensure accuracy and resolve anomalies.
- Develop deep expertise in data pipelines and platform architecture to serve as a subject matter expert for internal and external stakeholders.
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