Job Summary:

We are seeking an autonomous, technical Lead-Level Senior Data & BI Analyst to take ownership of our legacy data platform reverse-engineering and modern cloud analytics strategy. In this role, you will lead the technical decoding of legacy SQL Server Analysis Services (SSAS) multidimensional/tabular cubes and SQL Server Integration Services (SSIS) ETL packages, documenting critical business logic while facilitating our platform transition to Google Cloud Platform (GCP).

Key Responsibilities:

- Legacy Platform Reverse-Engineering: Lead the technical decoding, analysis, and reverse-engineering of legacy SSAS cubes, SSIS ETL packages, SSRS reports, and complex T-SQL stored procedures.

- Architecture & Business Logic Documentation: Create comprehensive, high-quality technical documentation detailing legacy data schemas, business calculation rules, data lineage, and system dependencies to guide cloud migration roadmaps.

- GCP Cloud Migration Partnership: Act as the primary Subject Matter Expert (SME) to guide Data Engineers in architecting and developing next-generation data solutions on Google Cloud Platform (GCP) using BigQuery, Cloud Composer (Airflow), Dataflow, and Dataproc (PySpark).

- MSBI Production Support & Tuning: Provide hands-on operational support, performance tuning, and troubleshooting for production Microsoft SQL Server environments, SSIS workflows, and SSAS data models.

- Advanced Analytics & Visualization: Design, build, and maintain ongoing metrics, interactive dashboards, and reporting tools using advanced visualization suites (Power BI, Tableau, Qlik, Dash Enterprise).

- Cross-Functional Business Engagement: Partner with business stakeholders, Finance/FinTech leads, and cross-functional teams to translate complex requirements into scalable analytical solutions and unified KPI definitions.

Tech Stack & Requirements:

- Core MSBI Stack: Proven, hands-on development and reverse-engineering mastery across Microsoft SSIS, SSAS, SSRS, T-SQL, and MS SQL Server.

- System Documentation: Demonstrated ability to analyze, reverse-engineer, and document complex, multi-tiered legacy data architectures.

- Data Modeling & Analytics: Strong experience in relational and dimensional data modeling, ETL design, and business data analysis.

- Tenure: 3 to 5 years of progressive, relevant experience in Data Engineering, Business Intelligence, or Analytics.

Preferred Qualifications:

- Domain Experience: Professional experience within the Finance / FinTech - IT domain.

- GCP Data Ecosystem: Operational familiarity or exposure to BigQuery, Cloud Composer (Airflow), Dataproc, PySpark, Dataflow, Terraform, or Tekton.

- Scripting: Hands-on scripting capability in Python or R for advanced data analysis and automation.