Senior Data Analyst

About the Opportunity
We are seeking a Senior Data Analyst who can own end-to-end data pipelines, ensure reporting accuracy at scale, and act as a trusted data partner to product, engineering, and business teams. The platform processes high-volume transactional, behavioral, and partner data that powers business intelligence, operational reporting, reconciliation, and analytics for internal teams and external stakeholders.
This role goes beyond dashboarding - you will design ETL workflows, influence data models, troubleshoot production issues, and mentor junior analysts in a complex, enterprise environment.
Role Overview
As a Senior Data Analyst, you will:
● Own and evolve enterprise-grade ETL pipelines and BI solutions
● Ensure data quality, consistency, and performance across platforms
● Design and deliver trusted reporting and analytics used for operational and business decisions
● Partner with engineering, DBAs, and cloud teams on data architecture and optimization
● Act as a senior point of escalation for data issues and reporting correctness
● Guide best practices and mentor junior team members
You will work across SQL Server–based systems and GCP-based cloud workflows, supporting both real-time and batch data use cases.
Key Responsibilities
1. ETL Architecture & Data Engineering
● Architect, design, and maintain complex SSIS ETL pipelines across multiple data sources
● Own data ingestion, transformation, and validation logic for large-scale datasets
● Optimize ETL performance for volume, reliability, and recoverability
● Implement robust data quality checks, reconciliation logic, and audit controls
● Lead troubleshooting and root-cause analysis for production data issues
● Support data migrations, platform integrations, and schema evolution
2. Business Intelligence & Analytics
● Design and maintain enterprise-grade SSRS reports used by business and operations teams
● Build and govern Power BI datasets and dashboards with consistent metrics and definitions
● Design and maintain SSAS cubes for multi-dimensional and historical analysis
● Ensure KPI definitions, aggregations, and calculations are accurate and aligned
● Partner with stakeholders to translate business questions into analytics solutions
3. Cloud, Automation & Integrations
● Design and implement Python-based automation for data processing and monitoring
● Work with GCP services including BigQuery, Cloud Functions, Cloud Scheduler, and Secret Manager
● Automate data pipelines, report refreshes, and operational checks
● Integrate third-party systems via APIs (e.g., JIRA, Zendesk, Matomo)
● Support hybrid architectures spanning on-prem and cloud environments
4. Leadership, Support & Collaboration
● Act as a senior escalation point for data and reporting issues
● Collaborate with DBAs on query optimization, indexing, and performance tuning
● Participate in production support and on-call rotations as required
● Define and maintain documentation, standards, and best practices
● Mentor junior analysts and review their ETL and reporting work
● Contribute to data governance, naming standards, and metric definitions