Senior Data Analyst (SQL/ETL)

ITR Group•Minneapolis, MN

2d•$62 - $82•Hybrid

About The Position

Contract consulting opportunity W2 hourly only (no C2C) Hybrid onsite (flexible) - Minneapolis, MN Work authorization status: US Citizen or GC holder Seeking a Senior Data Analyst to support a major Finance application modernization and data platform migration to a modern Google Cloud Platform (GCP) environment. This role will focus on data validation, reconciliation, variance analysis, reporting, and dashboard development as legacy Finance applications operate in parallel with modern platforms. You will work closely with engineering, product, Finance, business, and legacy-system teams to identify data discrepancies, determine root causes, document findings, and support critical Go-Live decisions . The ideal candidate is highly hands-on, analytical, and comfortable working through complex or ambiguous data problems independently. Strong candidates can explain not only what they did, but how they approached a problem and why they made specific technical decisions. This is a highly visible data quality and modernization initiative. Your analysis will help ensure that Finance data is accurately transitioned from legacy applications to the modern GCP-based platform and will provide stakeholders with the information needed to make informed Go-Live decisions .

Requirements

5+ years of hands-on SQL experience working with large-scale data platforms/databases such as Google BigQuery, Hadoop, or similar technologies.
3+ years of experience with ETL/data pipeline tools, such as Airflow, Informatica, dbt, or similar technologies.
Hands-on experience with Python and/or PySpark for data analysis and data processing.
Experience with data visualization and reporting tools such as Power BI, Looker, and/or LookML.
Strong experience with: Data validation and reconciliation, Source-to-target comparison, Variance detection and root-cause analysis, Duplicate and reject/error validation, Audit and control-total validation, Business-rule validation, Data quality analysis.
Ability to analyze and interpret data mappings, transformation logic, reporting requirements, data lineage, and data-quality rules.
Experience creating reconciliation reports, exception reports, validation summaries, defect documentation, and business sign-off materials.
5+ years of experience in a data analytics role.
3+ years of experience working in an Agile environment.
Strong communication and collaboration skills with technical and non-technical stakeholders.

Responsibilities

Develop complex SQL queries and datasets to compare legacy and modern application data and identify variances.
Perform data validation, reconciliation, duplicate detection, reject/error validation, audit/control-total validation, and business-rule validation.
Analyze mapping documents, transformation logic, reporting requirements, data lineage, and data-quality rules.
Investigate data discrepancies and collaborate with Product, Engineering, Finance, and Business teams to determine root causes.
Document identified variances, root causes, resolutions, and accepted exceptions.
Develop reconciliation reports, exception reports, validation summaries, defect logs, and business sign-off documentation.
Build dashboards and visualizations that communicate data variances, trends, KPIs, and reconciliation results.
Establish and monitor data-variance trends and assist stakeholders in determining appropriate tolerance thresholds for Go-Live decisions.
Use Python/PySpark for data analysis, processing, and data movement.
Work with ETL and data-pipeline technologies to understand and validate data transformations.
Participate in an Agile delivery environment, including user stories, acceptance criteria, sprint ceremonies, defect triage, and iterative delivery.
Support approximately two quarters of parallel operation between legacy and modern platforms.