Senior Data Analyst

Cloudious • Dallas, TX

3d

About The Position

The Senior Data Analyst will join a financial-services analytics program and focus on data discovery, profiling, and gap analysis across diverse enterprise data sources. The role determines what data is available, identifies and sources additional data, and finds missing data points needed to develop reliable business and management metrics. The analyst works with business stakeholders, metric owners, Data Architects, Data Engineers, and BI teams to define extraction scope and quality controls, and documents assessments, gaps, blockers, and dependencies.

Requirements

• 10+ years of data analytics experience.
• Strong SQL skills for data profiling and complex joins.
• Working knowledge of BigQuery and practical Python skills.
• Proven ability to discover and assess structured and semi-structured data across enterprise systems.
• Ability to decompose KPIs into source fields and document source-to-metric lineage.
• Experience analyzing source systems such as Jira, Rally, and GitHub, and working with various data formats.
• Experience defining data quality checks and producing comprehensive documentation.
• Ability to collaborate with stakeholders in regulated financial-services environments.

Nice To Haves

• Google Cloud certification or equivalent analytics certification.
• Experience with Power BI, Tableau, and ETL processes.
• Exposure to GCP services such as Cloud Storage, Dataflow, and Cloud Run.
• Understanding of Agile/Scrum methodologies and data-quality frameworks.

Responsibilities

• Perform data discovery and profiling across platforms including Jira, Rally, GitHub, Clarity, Remedy, and other enterprise sources.
• Document dataset availability, ownership, grain, keys, history, refresh cadence, access constraints, and suitability for metrics.
• Build and maintain a Data Availability Inventory and field-level gap assessment, classifying metric inputs as available, partially available, derivable, or missing.
• Use SQL, BigQuery, and Python to assess data completeness, uniqueness, validity, consistency, timeliness, distributions, outliers, and referential integrity.
• Analyze relationships across systems and define business keys, joins, mappings, code translations, hierarchies, precedence, and reconciliation rules.
• Decompose metrics into required fields, grain, dimensions, period logic, formulas, exclusions, targets, and organizational rollups.
• Create source-to-metric traceability from source fields through BigQuery transformations to semantic measures and reports.
• Collaborate with business stakeholders, metric owners, Data Architects, Data Engineers, and BI teams to define extraction scope and quality controls.
• Maintain Confluence documentation, data issue logs, UAT evidence, and concise status reports covering assessments, gaps, blockers, and dependencies.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed