Data Analyst

Insight Global; Juno Beach (FL); On-site; USD 90,000 - 130,000; Full time

Job summary

Insight Global is seeking a Data Quality Analyst / Databricks Implementation Specialist to drive governance, data quality, and Unity Catalog rollout in our enterprise Databricks lakehouse environment.

You will partner with data stewards, owners, and engineers to translate business needs into governed datasets, develop quality rules, perform profiling, and ensure metadata, lineage, and access controls are embedded across pipelines.

Qualifications

• 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.
• Support Unity Catalog rollout and metadata standards across domains.
• Embed lineage, ownership, and quality rules into Databricks pipelines.

Responsibilities

• Develop, document, and maintain data quality rules for critical data elements.
• 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.
• Support Unity Catalog rollout across domains and metadata standards.
• Assist onboarding domains into Bronze Silver Gold architecture.
• Ensure lineage and quality rules are embedded in Databricks pipelines.
• Implement domain-aligned access controls and sensitivity tagging.
• Work with data stewards to translate business meaning into standardized CDEs.

Skills

Data quality concepts

SQL

Data analysis

Data profiling

Root-cause analysis

Metadata management

Data governance

Tools

Databricks

Delta Lake

Unity Catalog

Job description

• 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.

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.

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.