Data Analyst

Hexaware Technologies

Atlanta, GA, United States

15 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Query Performance Amazon S3 Confluence JIRA Automation of Tests Business Intelligence Development Collaborative Software Data Validation Data Presentation Data Security Identity and Access Management Python (Programming Language)

+16 more

Oracle (Applications) Performance Tuning Query Optimization Software Tools Simple Data Format SQL Databases Tableau (Software) Parquet Sql Optimization GitHub Copilot Data Layers Pandas Statistics Packages AWS Glue Amazon Simple Queue Service (SQS) 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.