Business Data Analyst Python & PL/SQL

Artech LLC

  • Columbus OH, OH
  • 30+ days ago
  • $35–$43 Per Hour

Highlights

Role Overview: Business Data Analyst plays a hands-on role in understanding| modeling| and translating complex data from multiple source systems into trusted| analytics-ready data products that support business decision-making| regulatory reporting| and AI/analytics use cases. 2. Data Profiling & Data Quality Perform detailed data profiling on new and existing data sets (nulls| distributions| outliers| code sets| pattern and length analysis) using SQL and other tools to identify issues and opportunities.

Numbers & Facts

LocationColumbus OH, OH
Salary$35–$43 Per Hour

Description

Request ID: 94508-1
Title: Business Data Analyst – Python & PL/SQL

Locations: Remote: Columbus OH
Duration: 6+ Months with Possible Extension.
Pay Range: $35 -$43/Hour on W2/C2C (All inclusive)

 
Job Descriptions:
Skills: Python, PL/SQL, Data Concepts & Data Modelling
Experience Required: 6-8 Years
 
Role Overview: Business Data Analyst plays a hands-on role in understanding| modeling| and translating complex data from multiple source systems into trusted| analytics-ready data products that support business decision-making| regulatory reporting| and AI/analytics use cases.

Key Responsibilities
1. Data Analysis & Modeling
  • Analyze complex data from multiple source systems to understand entities| relationships| business rules| and usage patterns (e.g.| policy| claims| finance| partner data).
  • Contribute to conceptual and logical data models for key domains| working in partnership with data architects and data modelers.
  • Recommend modeling patterns (e.g.| relational| dimensional) appropriate for warehouses| marts| and operational data stores| ensuring models are usable by downstream analytics and AI workloads.
  • Review and provide feedback on model changes| ensuring that naming| keys| cardinality| and business definitions are consistent and well documented.
 
2. Data Profiling & Data Quality
  • Perform detailed data profiling on new and existing data sets (nulls| distributions| outliers| code sets| pattern and length analysis) using SQL and other tools to identify issues and opportunities.
  • Summarize profiling results in clear| consumable formats (tables| visuals| narratives) that explain data quality risks and their impact on business value and delivery scope.
  • Partner with data stewards| product owners| and engineers to translate profiling findings into data quality rules| checks| and monitoring requirements for pipelines and data products.
  • Support Trusted Data / AI-ready objectives by ensuring that quality expectations| thresholds| and controls are explicitly defined and testable for the assets you support.
 
3. Source Target Mapping & Design
  • Lead or co-lead source target mapping for new data products and migrations| especially where legacy systems and cross-domain data need to be reconciled.
  • Validate mapping choices against business requirements| data types| formats| and constraints; identify and document transformation| derivation| and standardization logic.
  • Define and document completeness and reconciliation approaches (e.g.| row counts| hash totals| key coverage) that engineers and testers can automate in pipelines and tests.
  • Work closely with data engineers to ensure mappings are feasible| performant| and aligned to data golden-path patterns from raw harmonized curated zones.
 
4. Collaboration
  • Delivery & Run Participate actively in backlog refinement| design reviews| and sprint ceremonies to clarify data requirements| acceptance criteria| and non-functional needs (e.g.| latency| freshness| lineage| access controls).
  • Provide clear analytical input to estimates| tradeoffs| and risk assessment for stories and epics involving data sourcing| modeling| and mapping.
  • Support testing by defining test data needs| validating mapping implementations| and reviewing defects related to data issues (values| joins| business rules).
  • Contribute to incident/root-cause analysis for data issues and partner with engineering teams on durable fixes (not just one-off corrections).
 
5. Governance| Metadata & Documentation
  • Create and maintain high-quality documentation for data definitions| mapping
 
Company Benefits & Culture
  • Inclusive and diverse work environment
  • Opportunities for professional growth and development
  • Comprehensive health and wellness benefits

Appreciate your quick response and please feel free to reach me out for any query you may have.

Thanks

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