Data Analyst

Here Technologies
Atlanta, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Atlanta, United States of America

Tech stack

Query Performance
Amazon Web Services (AWS)
Confluence
JIRA
Automation of Tests
Business Intelligence
Collaborative Software
Data Validation
Data Presentation
Data Security
Identity and Access Management
Python
Oracle Applications
Performance Tuning
Query Optimization
Software Tools
Simple Data Format
SQL Databases
Tableau
Parquet
Sql Optimization
GitHub Copilot
Data Layers
Pandas
Statistics Packages
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Software Version Control

Job description

  • Lead design and governance of core KPIs, metric definitions, and semantic layers.
  • Deliver complex analytical work using advanced SQL, including performance tuning on RDS/Oracle/Redshift and cost-conscious querying in Athena.
  • Use Python to create reproducible analysis (pandas, statsmodels/scikit-learn light use), automation scripts, and data validation checks.
  • Define data quality expectations; implement automated checks and anomaly detection; triage and drive resolution with engineering.
  • Conduct deep-dive analyses, cohorting, funneling, forecasting, and experiment design.
  • Create and maintain STTM Mapping document by coordinating with upstream/downstream stakeholders
  • Improve query performance with sort keys, distribution keys, partitioning, predicate pushdown, and compression awareness.
  • Establish version control and peer-review processes for analytics assets; contribute to lightweight CI for SQL/tests.
  • Mentor analysts; review artefacts for accuracy, clarity, and business relevance.
  • Partner with data engineers and product teams on data contracts, schema evolution, and roadmap priorities.

Requirements

  • Expert SQL on RDS/Oracle/Redshift (query tuning, vacuum/analyze awareness) and Athena (partitions, file formats, cost control).
  • Advanced BI development and data storytelling; strong UX best practices for dashboards.
  • Python for analysis and automation; packaging and reusability of common analytics functions.
  • Solid statistics for inference and experiment design; practical application in business contexts.
  • Deep understanding of data modeling, dimensional design, and semantic layers.
  • Collaboration tools (Confluence/Jira), stakeholder management, and ability to translate business needs into robust analytical solutions.

Nice-to-Have

  • Experience with modeling tools; governance of analytics layers.
  • Familiarity with AWS Glue Data Catalog, IAM basics for data access, and S3 file formats (Parquet/ORC).
  • Exposure to event-based data (Kinesis/SNS/SQS) and data freshness SLAs.
  • Build scalable, reusable dashboards and data models in QuickSight/Tableau; enforce consistency and naming standards.
  • Good understanding of using AI tools like Github Copilot or similar for code productivity
  • Familiarity with Secondary mortgage industry is preferred.

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