Senior Data Analyst - Python/SQL/ETL

Role Overview :

- Design, implement, and optimize ETL pipelines using SQL, Python, and workflow automation tools.

- Manage structured and semi-structured datasets including API-driven logs, transactional data, and operational event streams.

- Apply principles of data modeling, indexing, partitioning, and query optimization to ensure high performance.

- Establish error handling, data validation, and monitoring frameworks for robust data pipelines.

Analytics & Business Intelligence :

- Develop advanced Power BI dashboards with role-based security, optimized DAX queries, and high performance on large datasets.

- Automate data refresh cycles and implement parameterized dashboards for scalability across categories.

- Apply statistical and algorithmic techniques in Python for anomaly detection, forecasting, and trend analysis.

Operational & API Analytics :

- Work on real-time API logs to analyze order lifecycle behavior, SLA compliance, and system bottlenecks.

- Build scoring frameworks (e.g., NP scorecards, SLA compliance indices) to evaluate partner and category performance.

- Integrate external APIs and develop data ingestion pipelines to enrich operational analytics.

Collaboration & Technical Leadership :

- Partner with engineering and product teams to ensure data availability, consistency, and scalability across systems.

- Define best practices for query performance, BI reporting, and Python-driven automation.

- Mentor junior analysts in writing efficient SQL, structuring pipelines, and building production-ready dashboards.

Candidate Profile :

Education :

- Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related quantitative field.

- Strong grounding in data structures, algorithms, and database design principles.

Technical Skills :

- SQL / PostgreSQL : Advanced queries, query optimization, window functions, indexing, schema design.

- Python : Data manipulation (Pandas, NumPy), automation scripts, API integrations, basic statistical modeling.

- Power BI : DAX queries, role-level security, drill-through reports, performance tuning, visualization best practices.

- ETL / Data Pipelines : Workflow orchestration, incremental loads, error handling, data versioning.

- APIs & Logs : Parsing, transforming, and analyzing event-driven or JSON-based datasets.

- Excel (Advanced) : Complex formulas, pivoting, modeling for ad-hoc analysis.