Role Overview :
We are looking for a Senior Data Analyst with strong computer science fundamentals and expertise in SQL, Power BI, Python, and ETL pipeline engineering. The role requires deep technical capability to build reliable data systems, process large-scale transactional datasets, and optimize analytics infrastructure for real-time decision-making.
Key Responsibilities :
Data Engineering & ETL :
- 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.(ref : hirist.tech)