Data Analyst

Required Skills & Experience Required Qualifications • 3–5 years of experience in data quality, data governance, or data analysis. • Hands-on experience with Databricks, Delta Lake, or similar cloud platforms. • Strong understanding of data quality concepts. • Experience with metadata catalogs or governance tools. • Proficiency with SQL and data analysis. • Strong communication skills. Job Description The Data Quality Analyst / Databricks Implementation Specialist plays a key role in advancing the company’s enterprise data governance and Databricks Lakehouse strategy. This role partners closely with business data stewards, data owners, and technical teams to translate business data requirements into governed, high-quality datasets within Databricks Unity Catalog. The analyst will support domain onboarding, develop and operationalize data quality rules, perform profiling and analysis, and help implement enterprise standards for metadata, lineage, and semantic consistency. Data Quality & Profiling • Develop, document, and maintain data quality rules for critical data elements (CDEs). • Perform data profiling, anomaly detection, and root-cause analysis. • Partner with data stewards to validate definitions, thresholds, and business rules. • Monitor and report on data quality metrics and remediation progress. Databricks Unity Catalog Implementation • Support Unity Catalog rollout across domains, including catalog structure, tagging, and metadata standards. • Assist with onboarding domains into the Bronze → Silver → Gold architecture. • Ensure lineage, ownership, and quality rules are embedded into Databricks pipelines. • Help implement domain-aligned access controls and sensitivity tagging. Collaboration with Data Stewards & Business Partners • Work directly with business data stewards to understand data requirements and quality expectations. • Translate business meaning into standardized CDEs and steward-approved metadata. • Facilitate working sessions to align on semantics, domain boundaries, and data product requirements. • Support consistent governance practices across domains. Metadata, Lineage, and Catalog Management • Maintain high-quality metadata in the enterprise data catalog. • Ensure CDEs, KPIs, and domain terms are accurately documented. • Validate lineage from raw sources through refined layers. Data Analysis & Issue Resolution • Investigate data issues raised by business users or downstream consumers. • Perform impact analysis for schema changes or quality rule updates. • Support remediation efforts with engineering and business teams.