Senior Data Analyst, Data Transfer Agreement, Gap Analysis, Data SQL Skills

Data Transfer Agreements

Author, maintain, and update Data Transfer Agreements (DTAs) for all client and partner data-sharing arrangements.

Collaborate with legal, compliance, and IT security to ensure DTAs reflect current data flows, retention policies, and regulatory requirements.

Serve as subject matter expert on DTA scope during client onboarding and contract renewals.

Track DTA revision history and surface expiration or gap alerts proactively.

Gap Analysis

Lead structured gap analysis between presentation DB views, Scriptly schema, and source system data to identify coverage, mapping, and quality gaps.

Produce clear gap analysis documentation with prioritized remediation recommendations for data engineering and product teams.

Monitor ongoing gap metrics and communicate trends to stakeholders via dashboards and regular reports.

Translate gap findings into actionable data quality requirements and DTA scope adjustments.

Customer Engagement

Serve as a direct client-facing resource for data-related inquiries, onboarding, and ongoing reporting needs.

Lead client-facing data reviews, walking stakeholders through findings, gaps, and resolution timelines.

Build trusted relationships with customer data teams, acting as an interpreter between business requirements and technical data architecture.

Gather and document client data requirements, translating them into analytical specifications and DTA updates.

Data & SQL Skills

Own complex SQL queries, data modeling, and analytical reporting across Snowflake and connected data warehouse environments.

Write optimized SQL queries (Snowflake/SQL Server) for complex data extraction, transformation, and validation across the integrated data environment.

Design and maintain reporting solutions and dashboards for client and internal stakeholders.

Interpret data, formulate findings, and deliver concise, well-structured reports and presentations.

Validate data quality by filtering, cleansing, and cross-referencing datasets against known schema mappings.

Apply statistical techniques to analyze trends, outliers, and performance indicators.

Develop and maintain data documentation including data dictionaries, field-level lineage maps, and integration runbooks.

Identify and propose process improvement opportunities based on gap analysis and customer feedback.

Support continuous improvement of data collection, mapping, and quality control workflows.