Senior Data Analyst, SQL

GIGABIT Technologies Private Limited

. Lead analytics initiatives from requirements gathering and data preparation through analysis, dashboard delivery, and recommendations .

Posted 10/27/2026full-timeRemoteSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced SQL, data visualization tools like Power BI or Tableau, and statistical analysis techniques. Proficient in data modeling, validation, and governance, with a strong ability to lead analytics initiatives and collaborate across teams.

Highest-signal resume keywords

Advanced SQLPower BIData ModelingPythonData Validation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced SQLData ModelingPythonDescriptive StatisticsInferential StatisticsExploratory Data AnalysisData ValidationAdvanced ExcelETL/ELT PipelinesStatistical Analysis

Soft Skills

MentoringCollaborationProblem-SolvingCommunication

Tools & Technologies

Power BITableauLookerGitDAXPower QueryLookML

Industry Keywords

Data GovernanceKPI DefinitionMetric DocumentationData AccuracyAnalytical Lifecycle

Tech Stack

Tools & technologies

ETLPythonSQLTableau

About the role

Key responsibilities & impact

Lead analytics initiatives from requirements gathering and data preparation through analysis, dashboard delivery, and recommendations
Define and maintain KPIs, metric definitions, and reporting standards aligned with business objectives
Investigate trends, segments, and customer or product behavior to identify opportunities and inform priorities
Build reusable analytical datasets and automate recurring analyses and reporting workflows
Ensure data accuracy and consistency through validation, reconciliation, and discrepancy investigation
Partner with Product, Engineering, and Delivery teams to clarify needs, resolve dependencies, and address information gaps
Make technical decisions independently, explain trade-offs, and escalate significant risks
Review analytical deliverables, mentor colleagues, and improve documentation and reusable practices
Apply data privacy, access, and governance controls throughout the analytical lifecycle

Requirements

What you’ll need

Advanced SQL: complex joins, CTEs, window functions, aggregations, query optimization, and execution plan analysis
Proficiency in Power BI, Tableau, or Looker, including DAX, Power Query, LOD, LookML, connections, filters, drill-downs, and optimization
Data modeling: granularity, fact/dimension tables, relationships, and reusable semantic models
Python or R for data cleaning, analysis, visualization, and maintainable scripts
Descriptive and inferential statistics, sampling, hypothesis testing, regression, bias detection, and correlation vs. causation
Exploratory data analysis, segmentation, cohort analysis, trend analysis, and performance-driver identification
Data validation, source reconciliation, metric documentation, and data lineage
Advanced Excel formulas, pivot tables, lookups, and data preparation
Knowledge of ETL/ELT pipelines, data warehouses, update dependencies, latency, and schema changes
Git, peer review, reproducible analysis, and technical documentation
Role-based access control, sensitive-data handling, and secure distribution of analytical results

Benefits

Comp & perks

An exciting growth journey and a never-ending ambition to develop as a company
A friendly, supportive and humble working culture where the team always comes first
Opportunities for professional development and personal growth
Passionate, high-performing and genuine colleagues
Results and well-being prioritized
Referral reward if a recommended friend or colleague is hired
15 business days PTO and flexibility program
Local holidays
Remote work — work from anywhere
Notebook
Monday–Friday work hours, 8 a.m.–5 p.m.