Data Analyst

Job Description

• Maintain data accurately and efficiently across platforms including CRMs (LeadSquared, Zoho) and Google Sheets / Excel
  

• Update and manage recurring reports, ensuring data integrity, consistency, and timely delivery to stakeholders
  

• Build and maintain dashboards using tools such as Looker Studio, Zoho Analytics, Metabase or Power BI
  

• Identify and resolve data discrepancies, anomalies, and root-cause issues – not just surface-level fixes
  

• Ensure reporting logic is transparent, accurate, and trusted by business teams
  

2. Data Modelling & Database Architecture

• Design and maintain clean, well-structured database schemas that serve as a reliable single source of truth
  

• Apply strong data modelling principles – normalisation, dimensional modelling, and entity-relationship design – to support scalable data systems
  

• Make informed architectural decisions around data structures, identifiers, historical vs. current data management, and schema evolution
  

• Ensure data consistency, referential integrity, and reliability across all interconnected systems
  

• Document data models, schema definitions, and architectural decisions to enable long-term maintainability
  

• Collaborate with engineering and operations teams to align database design with business reporting and automation needs
  

3. ETL Pipelines & Data Orchestration

• Build, manage, and monitor ETL (Extract, Transform, Load) pipelines to move and transform data across systems reliably
  

• Work with orchestration tools such as Apache Airflow, Airbyte, or similar platforms to schedule and manage data workflows
  

• Use Python or SQL for data extraction, transformation, validation, and loading into target systems
  

• Integrate data sources using APIs and webhooks to ensure seamless, automated data flow
  

• Optimise pipelines for performance, reliability, and cost efficiency; implement error handling, retries, and alerting
  

• Proactively monitor pipeline health and resolve failures or data quality issues before they impact downstream reporting
  

4. SQL & Data Analysis

• Write and optimise advanced SQL queries for operational and analytical use cases
  

• Extract, clean, and analyse data from relational databases (PostgreSQL, MySQL, BigQuery, or similar)
  

• Perform data validation and transformation to support accurate downstream reporting
  

• Analyse data to identify patterns, trends, and actionable insights for business teams
  

Must-Have

• 2–3 years of relevant experience in data analysis, analytics engineering, or a related role
  

• Strong proficiency in SQL – ability to write complex, optimised production-grade queries including joins, window functions, CTEs, and subqueries
  

• Solid understanding of data modelling principles – normalisation, dimensional modelling, and relational database design
  

• Hands-on experience with database architecture – designing schemas, managing identifiers, and structuring data for both operational and analytical use
  

• Experience with ETL tools or orchestration platforms such as Apache Airflow, Airbyte, Prefect, or similar
  

• Hands-on experience with at least one reporting / BI tool: Looker Studio, Power BI, Zoho Analytics, Tableau, or similar
  

• Proficient in Microsoft Excel and/or Google Sheets, including formulas, pivot tables, and data validation
  

• Demonstrated ability to understand business requirements and convert them into structured, scalable data solutions
  

• Exposure to AI-assisted analytics, intelligent automation, or LLM-powered data workflows
  

• Strong attention to detail, data accuracy, and logical thinking
  

• Good communication and interpersonal skills for cross-functional coordination
  

• A degree in a relevant field (e.g. Statistics, Computer Science, Business Analytics, Commerce, or equivalent)
  

Should Have

• Experience working with CRM platforms such as LeadSquared, Zoho CRM, or Salesforce
  

• Exposure to cloud data platforms: GCP (BigQuery)
  

• Exposure to automation tools – Make (Integromat), n8n, Zapier, or Google Apps Script
  

• Familiarity with Python for data processing, transformation, and pipeline scripting
  

• Basic understanding of APIs, webhooks, and system integrations
  

• Ability to document data models, processes, and architectural decisions clearly
  

• Experience building or maintaining data pipelines in a production environment
  

Good to Have

• Experience with Apache Superset for self-serve analytics and dashboard creation
  

• Excel Macros or Google Apps Script development experience
  

• Exposure to cloud data platforms: AWS (Redshift / S3), or Azure (Synapse)
  

• Familiarity with dbt (data build tool) or similar transformation frameworks
  

• Structured and process-oriented thinker who sees patterns in chaos
  

• Thinks in systems and data models – not just individual queries or tasks
  

• Proactive ownership – you improve systems without waiting to be asked
  

• Genuine curiosity about data, databases, automation, and how businesses operate
  

• Curiosity about AI-assisted analytics, intelligent automation, or LLM-powered data workflows
  

• Strong problem-solving ability with a logical, methodical approach to challenges
  

• Collaborative team player who communicates clearly with both technical and non-technical stakeholders
  

• Willingness to learn and adapt quickly in a fast-paced environment