Position Overview

We are looking for a skilled and self-driven Data Analyst with 3–5 years of experience who can independently handle end-to-end analytics from querying raw data sources and building data models to delivering polished, visually compelling dashboards. The ideal candidate combines solid Tableau development expertise with data engineering exposure, including experience working with streaming/real-time data, semantic layers, and cloud-based data platforms (GCP/BigQuery).

Key Responsibilities
Data Modeling & Architecture

· Design and build dimensional data models (star schema, snowflake schema) optimized for analytical workloads

· Define fact and dimension tables, establish relationships, and manage slowly changing dimensions

· Build and maintain a semantic layer to provide consistent, business-friendly definitions of metrics and KPIs

· Create reusable, well-documented data models that serve as a single source of truth.

Data Querying & Engineering

· Write advanced SQL queries for data extraction, transformation, and validation across large-scale datasets

· Query data directly from source systems (databases, APIs, cloud storage, streaming platforms)

· Work with streaming/real-time data pipelines — understand event-driven architectures, time-windowed aggregations, and near-real-time refresh strategies

· Build and optimize Tableau Extracts and live connections for performance at scale

· Collaborate with data engineers on ETL/ELT pipelines, data quality checks, and pipeline monitoring

· Handle data at granular levels (minute-level, event-level) and aggregate appropriately for reporting.

Visualization & Dashboard Development

· Design and develop enterprise-grade Tableau dashboards that are visually appealing, intuitive, and standards-compliant

· Select the right chart type for the right data story:

► Time-series line charts for trends

► Heat maps for comparative/density analysis

► Bar/column charts for ranking and composition

► KPI cards and scorecards for executive summaries

► Scatter plots for correlation

► Geographic maps for spatial analysis

► Bullet charts and sparklines for compact performance views





· Follow data visualization best practices (Tufte principles, proper use of color, minimal chart junk, accessible design)

· Build interactive elements: cascading filters, parameters, drill-downs, tooltips, and dynamic actions

· Ensure dashboards are responsive, performant, and optimized for the target display resolution.

Performance Optimization

· Optimize dashboard load times through extract management, query efficiency, and calculated field optimization

· Apply best practices: reduce LOD complexity where possible, minimize blending, use context filters strategically

· Monitor and tune BigQuery query performance (partitioning, clustering, materialized views, slot usage)

· Manage extract refresh schedules and incremental extracts for large datasets.

Standards & Governance

· Establish and enforce visualization standards (color palettes, typography, layout grids, naming conventions)

· Maintain documentation for dashboards, data models, and metric definitions

· Ensure data accuracy and consistency across all reporting outputs

· Participate in peer reviews of dashboards and provide constructive feedback on design and logic.

Stakeholder Collaboration

· Gather requirements from business stakeholders and translate them into analytical solutions

· Present insights and recommendations to both technical and non-technical audiences

· Manage client feedback cycles — prioritize, implement, validate, and communicate changes

· Work independently to deliver end-to-end solutions with minimal supervision.

Required Skills

· 3–5 years of experience in Data Analytics, Business Intelligence, or a hybrid analyst/engineer role

· Tableau — advanced proficiency:

► LOD expressions, table calculations, parameters, sets, actions

► Dashboard layout, formatting, and UX best practices





► Tableau Server/Cloud publishing, extract management, permissions

· SQL — expert level:

► Complex joins, window functions, CTEs, subqueries, recursive queries

► Date/time manipulation, aggregation, and pivot logic

► Query optimization and execution plan analysis

· Data Modeling — solid understanding:

► Dimensional modeling (star/snowflake), normalization/denormalization

► Semantic layer concepts (metrics layer, business glossary, governed definitions)

· Google Cloud Platform (GCP):

► BigQuery — querying, partitioning, clustering, scheduling, cost management

► Cloud Storage — data lake staging and file management

► Basic understanding of Dataflow/Dataproc for pipeline awareness

· Streaming & Real-Time Data:

► Exposure to real-time or near-real-time data (Pub/Sub, Kafka, streaming inserts)

► Understanding of time-windowed aggregations and event-time vs processing-time

► Experience handling high-granularity data (minute-level, event-level)

· Strong understanding of data visualization principles and chart selection

· Experience working directly with source systems (databases, APIs, flat files, cloud storage)

· Ability to work independently and deliver complete solutions end-to-end.

Good to Have

· Experience with semantic layer tools (dbt metrics, Looker LookML, AtScale, or similar)

· Familiarity with Python or R for data wrangling and ad-hoc analysis

· Experience with Tableau Prep for data preparation workflows

· Knowledge of CI/CD for analytics (Git for SQL/Tableau, automated testing)

· Exposure to Agile/Scrum methodologies

· GCP Professional Data Analyst or Data Engineer certification

· Tableau Desktop Specialist / Certified Data Analyst certification

· Experience in media, broadcasting, healthcare, or other data-intensive domains

· Understanding of data governance frameworks and data cataloging.

Qualifications

· Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field.

· Relevant Tableau and/or GCP certifications (preferred).

Work Location: In person

📌 SAP Associate (India)
🏢 SAVISHTY
📍 India