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Tableau Developer
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Gurgaon
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About Us
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We empower enterprises globally through intelligent, creative, and insightful services for data integration, data analytics and data visualization.
Hoonartek is a leader in enterprise transformation, data engineering and an acknowledged world-class Ab Initio delivery partner.
Using centuries of cumulative experience, research and leadership, we help our clients eliminate the complexities & risk of legacy modernization and safely deliver big data hubs, operational data integration, business intelligence, risk & compliance solutions and traditional data warehouses & marts.
At Hoonartek, we work to ensure that our customers, partners and employees all benefit from our unstinting commitment to delivery, quality and value. Hoonartek is increasingly the choice for customers seeking a trusted partner of vision, value and integrity
How We Work?
Define, Design and Deliver (D3) is our in-house delivery philosophy. It’s culled from agile and rapid methodologies and focused on ‘just enough design’. We embrace this philosophy in everything we do, leading to numerous client success stories and indeed to our own success.
We embrace change, empowering and trusting our people and building long and valuable relationships with our employees, our customers and our partners. We work flexibly, even adopting traditional/waterfall methods where circumstances demand it. At Hoonartek, the focus is always on delivery and value.
Job Description
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1. Role Purpose
The Tableau Developer will provide production support, defect resolution, approved minor enhancements and continuous improvement for existing Tableau dashboards and reports within the WMS Analytics track. The role is responsible for dashboard availability, refresh reliability, data accuracy, reconciliation integrity and performance, while coordinating with upstream data-model and pipeline teams when issues originate outside Tableau.
2. Key Responsibilities
- Production monitoring: Monitor Tableau dashboard availability, scheduled refreshes, extract status and data-completeness indicators; identify failures, delays or stale data and coordinate timely recovery.
- Dashboard incident resolution: Investigate and resolve defects such as unavailable dashboards, refresh failures, incorrect calculations, broken filters, missing data, inconsistent totals and presentation-layer issues.
- Data validation and reconciliation: Compare dashboard outputs with approved source datasets or reporting models, analyse mismatches and reconciliation discrepancies, and isolate whether the issue is in Tableau or an upstream dependency.
- Bug fixing: Implement durable fixes in Tableau workbooks, calculations, parameters, filters, data-source mappings and dashboard logic without altering approved business rules.
- Minor enhancements: Deliver approved changes to existing dashboards, including fields, filters, calculated measures, parameters, layouts, views and reconciliation logic within the agreed fixed scope.
- Performance and technical-debt reduction: Optimise dashboards, data sources, calculations and refresh patterns to improve load time, stability, usability and maintainability.
- Release and regression validation: Test fixes and enhancements, validate data parity, support controlled deployment and verify dashboard behaviour after release.
- Root-cause analysis: Prepare RCA documentation for significant or recurring incidents, covering impact, cause, corrective action, preventive action and dependencies.
- Stakeholder coordination: Work with business users, analytics teams, dbt/PySpark developers, Airflow support and platform teams to resolve dashboard and upstream data issues.
- Governance and documentation: Maintain issue trackers, weekly status inputs, monthly governance inputs, dashboard support notes, runbooks and knowledge-handover material.
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Job Requirement
3. Required Technical Skills
- Tableau dashboard development and support: Strong hands-on experience building, maintaining, debugging and supporting production Tableau dashboards and reports.
- Tableau calculations and interactivity: Proficiency with calculated fields, table calculations, parameters, filters, sets, level-of-detail expressions and dashboard actions.
- Tableau data connectivity and refreshes: Experience working with published data sources, extracts and live connections, and troubleshooting refresh or data-source issues.
- SQL and data validation: Strong SQL capability for joins, aggregations, window functions, source-to-report checks, data-completeness analysis and defect investigation.
- Dashboard performance optimisation: Ability to diagnose slow dashboards and improve workbook design, calculations, data-source usage and refresh efficiency.
- Reconciliation and data quality: Ability to validate totals, identify duplicates or missing records, analyse source-to-dashboard mismatches and protect reporting accuracy.
- Production support and SLA handling: Experience prioritising business-impacting incidents, providing workarounds, performing RCA and delivering permanent fixes within agreed timelines.
- Testing, documentation and communication: Ability to perform regression validation, document changes and clearly communicate incident status, risks, blockers and resolution details.
4. Good-to-Have Skills
- Working knowledge of dbt and upstream analytics data models.
- Working knowledge of PySpark / Apache Spark and distributed data processing.
- Experience with Apache Airflow and CI/CD-based release processes.
- Hive or Hive-compatible data warehousing experience.
- Metabase dashboard and report support experience.
- Tableau Server or Tableau Cloud administration and content-governance exposure.
- Experience with WMS, SCM, inventory, transfer orders, shipment, installation, capitalization or fixed-asset analytics.
5. Functional and Operational Capabilities
- Ability to understand existing dashboard logic and translate business issues into Tableau-, data-source- or upstream-model-level fixes.
- Structured troubleshooting across source data, reporting models, refresh schedules, Tableau data sources, workbooks and dashboards.
- Strong attention to data accuracy, reconciliation integrity, performance and regression prevention.
- Ability to distinguish defects, minor enhancements and out-of-scope redesign requests.
- Strong ownership of production issues and a quality-focused approach to testing and controlled deployment.
- Clear written and verbal communication for incident updates, RCA reviews, blockers, risks and delivery status.
