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Data Analyst

BitwiseUnited States🇺🇸United StatesPosted Oct 7, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
23 hours ago
SQLETL

Job Description

Data Analyst

Fulltime 

Remote

Role Summary: 

We are seeking a Data Analyst to support a data and reporting modernization assessment. The role owns the technical analysis: inventorying and profiling reports, cubes and ETL pipelines, and producing Source-to-Target Mappings, data lineage and dependency documentation. The analyst works alongside the Business Systems Analyst, Solution Architects and data leaders, who validate the business definitions/requirements. 

Job Description:

  • Create Source-to-Target Mapping (STTM) documentation and perform dependency analysis. 

  • Inventory, assess and classify reports, cubes and reporting assets, including technical profiling. 

  • Review existing reports and cubes to understand and document the data mappings and data models. 

  • Inventory ETL pipelines and assess them for rationalization and standardization. 

  • Collaborate with ETL and data warehouse teams (Informatica) to understand transformation logic and document data mappings, data flows and dependencies. 

  • Document data lineage and perform impact analysis across sources, pipelines and reports. 

  • Support stakeholder workshops on data flows and mappings. 

  • Gather data requirements from business users and translate them into technical specifications. 

  • Perform data profiling and analysis using SQL to assess data quality and identify anomalies. 

  • Write and optimize SQL queries across source and target systems to validate the data. 

  • Analyze large datasets to identify trends, patterns, mapping gaps and data quality issues, and summarize findings for stakeholders. 

  • Define and apply data quality checks and validation rules across sources and targets. 

  • Validate data across systems and support testing and reconciliation. 

  • Perform root cause analysis on data discrepancies, data modeling issues and work with data engineering and project teams to address them. 

  • Document data definitions, mappings and findings for the team. 

  • Contribute to data governance by maintaining metadata, data dictionaries and naming standards. 

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