Data Analyst

We are looking for a highly skilled, hands-on Data Analyst / BI Developer who is exceptional in Tableau and even stronger in advanced SQL and data understanding. The role will own the complete analytics lifecycle—from understanding a business question and validating source data to building optimized SQL datasets and publishing reliable, decision-ready Tableau dashboards.

The successful candidate must be able to work independently with large, complex datasets, identify data-quality issues, explain the business meaning behind numbers, and convert analysis into clear, actionable insights. Strong Python development capability is required. DBMS experience and/or React knowledge will be an added advantage.

KEY RESPONSIBILITIES

• Partner with business and functional teams to understand processes, KPIs, reporting requirements, decision points, and data definitions.

• Design, develop, publish, and maintain enterprise-grade Tableau dashboards, reports, and reusable data sources.

• Build efficient and reliable SQL queries for complex analysis, reconciliation, reporting, and data preparation.

• Investigate data discrepancies by tracing data from source systems through transformations to final dashboards.

• Define data grain, joins, business rules, metric logic, filters, and exception-handling rules before visualization.

• Optimize Tableau workbooks, extracts, live connections, calculations, and underlying SQL for performance and scalability.

• Develop Python-based utilities and workflows for data extraction, transformation, validation, automation, API integration, and recurring analysis.

• Perform exploratory analysis, identify trends and anomalies, and communicate findings in simple business language.

• Create documentation covering metric definitions, data lineage, dashboard logic, refresh schedules, assumptions, and known limitations.

• Apply appropriate access controls, row-level security, testing, version control, and deployment practices.

• Support users after release, troubleshoot production issues, and continuously improve dashboards based on usage and feedback.

• Coach stakeholders and team members on effective dashboard use and sound interpretation of data.

MANDATORY TECHNICAL SKILLS

1. Exceptional Tableau expertise

• Deep hands-on knowledge of Tableau Desktop and Tableau Server/Cloud.

• Expert-level capability in calculated fields, Level of Detail (LOD) expressions, table calculations, parameters, sets, context filters, dashboard actions, data blending/relationships, and reusable data sources.

• Strong understanding of extracts versus live connections, refresh strategy, row-level security, publishing, permissions, subscriptions, and dashboard governance.

• Proven ability to create clean, intuitive, executive-ready dashboards without compromising analytical depth.

• Strong Tableau performance-tuning skills, including reducing query load, optimizing calculations, improving workbook design, and using performance diagnostics.

2. Expert-level advanced SQL

• Excellent command of complex joins, CTEs, subqueries, window functions, conditional aggregation, set operations, pivots/unpivots, date logic, and advanced analytical queries.

• Ability to write accurate SQL for large datasets while handling duplicates, nulls, changing master data, incomplete records, and different levels of granularity.

• Strong understanding of query execution plans, indexing, partitioning, views/materialized views, and performance optimization.

• Ability to independently reconcile results across source tables and prove the correctness of reported numbers.

• Sound knowledge of relational database concepts, normalization, dimensional modelling, fact/dimension design, and data marts.

3. Strong data and business understanding

• Ability to translate an unclear business requirement into precise questions, definitions, source mappings, and acceptance criteria.

• Strong understanding of data quality, data lineage, master data, transaction data, historical versus current-state reporting, and source-of-truth controls.

• Ability to distinguish correlation from causation, validate assumptions, identify anomalies, and explain why a metric changed—not only what changed.

4. Python development

• Strong hands-on Python skills for data processing and automation.

• Experience with pandas, NumPy, database connectivity, REST APIs, file processing, logging, exception handling, and reusable modular code.

• Ability to build and maintain ETL/ELT utilities, validation scripts, scheduled workflows, and analytical prototypes.

• Familiarity with Git, code review, testing, and maintainable development practices.

PREFERRED / ADDED ADVANTAGE

• DBMS expertise, including schema design, indexing, EXPLAIN/EXPLAIN ANALYZE, functions, views, materialized views, and database performance tuning.

• React knowledge for building lightweight analytical applications, integrating dashboards, or creating custom data-driven user interfaces.

• Exposure to data warehouses, cloud data platforms, orchestration tools, APIs, and modern data pipelines.

• Experience working with operational, sales, finance, supply-chain, or manufacturing data will be useful.

QUALIFICATIONS AND EXPERIENCE

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, Engineering, or a related discipline.

• Demonstrable experience delivering production Tableau solutions and writing complex SQL in a business environment.

• A strong portfolio or practical examples of dashboards, SQL problem-solving, performance tuning, and data reconciliation will be preferred.