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Part-Time Data Analyst (Power BI + SQL + Google Sheets)
Part-Time Data Analyst (Power BI + SQL + Google Sheets)StrategyCFO • Hyderabad, IN
Part-Time Data Analyst (Power BI + SQL + Google Sheets)

Part-Time Data Analyst (Power BI + SQL + Google Sheets)

StrategyCFO • Hyderabad, IN
1 day ago
Job description

Part-Time Data Analyst & Power BI Developer (with Data Engineering Skills)

Location : Remote (India)

Engagement : Part-Time (15–25 hours / week to start)

Company : StrategyCFO

Compensation : Competitive, based on skill and experience

About the Role

StrategyCFO is looking for a part-time, highly skilled Data Analyst who can independently own analytics and reporting work across Power BI, SQL, Google Sheets, and basic data engineering / integration tasks.

You will support multiple ongoing client projects by building dashboards, automating data flows, cleaning and modelling real-world datasets, and ensuring that reporting is accurate, reliable, and scalable.

This role is ideal for someone who prefers part-time, flexible hours, and enjoys building solutions end-to-end without heavy supervision.

🔹 Key Responsibilities

1. Power BI Development (End-to-End Ownership)

Develop dashboards from scratch (data ingestion → cleaning → modelling → DAX → visuals)

Use Power Query for data transformation and shaping

Build well-structured, analytics-ready data models (star schema)

Write advanced DAX for KPIs, time-intelligence, and business logic

Configure RLS, scheduled refresh, incremental refresh, parameters, etc.

Optimise dashboards for performance and accuracy

2. SQL (Intermediate to Advanced)

Write clean, optimized queries combining multiple datasets

Build logic for de-duplication, grouping, time-based metrics, trend analysis

Perform date / time conversions, timestamp harmonization, and business-rule logic

Help clean and prepare backend datasets for Power BI

3. Google Sheets + Automation

Work with operational data stored in Google Sheets

Use advanced formulas (QUERY, FILTER, ARRAYFORMULA, REGEX, etc.)

Structure Sheets for ingestion into Power BI

Automate repetitive steps using Apps Script (or willingness to learn quickly)

Build helper / staging sheets for data cleaning and QA

4. Data Engineering Foundations (Lightweight but Practical)

Integrate external systems through REST APIs (JSON, tokens, pagination)

Use Make.com / Pipedream / Apps Script to automate data ingestion

Normalize unstructured SaaS data into clean analytics tables

Troubleshoot data flow breaks and ensure continuity of pipelines

5. Data Cleaning, Structuring & Documentation

Clean messy, real-world datasets (duplicates, mismatches, missing fields)

Design clear transformation logic from raw data → final model

Document data definitions, modelling rules, and key assumptions

Provide quality checks to ensure stable reporting

🔹 Required Skills

Technical

Strong Power BI skills (DAX, modelling, relationships, Power Query)

SQL (joins, aggregations, window functions, transformation logic)

Google Sheets (advanced formulas and structuring)

API integrations (JSON handling, endpoints, authentication)

Automation tools (Make.com, Apps Script, Pipedream or similar)

Analytical

Ability to interpret real-world business datasets

Strong logical thinking and ability to design KPIs

Good pattern recognition and data storytelling

Soft Skills

Works independently with minimal guidance

Strong attention to detail

Comfortable with asynchronous communication

Ability to meet deadlines in a part-time schedule

🔹 Preferred (Not Mandatory)

Experience with CRMs, ERPs, or accounting systems (e.g., Odoo, Xero, Dear, JobNimbus, Shopify)

Exposure to multi-system data integration

Python for data automation (nice to have)

Prior part-time / consulting / freelance experience

🔹 Engagement Details

Part-time role to start (15–25 hours / week)

Flexible working hours (IST)

Remote-only

Option to convert to long-term / ongoing engagement based on performance

Work spans multiple industries (e-commerce, solar, home improvement, FMCG, etc.)

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Data Analyst Power Bi • Hyderabad, IN

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