- Data Analyst 🔹 Primary Responsibilities
Collect, clean, and analyze data to help make business decisions
Create dashboards and reports using BI tools
Identify trends, patterns, and outliers in data
Communicate findings to stakeholders with visualizations
🔹 Key Skills
SQL
Excel
Data visualization (Tableau, Power BI)
Basic statistics
🔹 Tools
SQL, Excel
Tableau, Power BI
Python/R (for advanced analytics)
Google Analytics (in marketing)
🔹 Typical Career Path
Data Analyst → Senior Data Analyst → Analytics Manager → Director of Analytics
I was looking into some learning options and came across this data analytics course based in Pune — sharing in case it helps someone:https://technogeekscs.com/courses/data-analytics-courses-pune
- Business Analyst 🔹 Primary Responsibilities
Bridge the gap between business needs and data insights
Translate business problems into analytical questions
Collaborate with stakeholders to define KPIs
May perform light data analysis
🔹 Key Skills
Business acumen
Communication & documentation
Data interpretation
Requirements gathering
🔹 Tools
Excel, PowerPoint
SQL (basic)
Tableau/Power BI (for reports)
Jira, Confluence (for documentation)
🔹 Typical Career Path
Business Analyst → Product Manager / Business Intelligence Manager / Strategy Lead
- Data Scientist 🔹 Primary Responsibilities
Build predictive models and machine learning algorithms
Perform deep statistical analysis and A/B testing
Work with unstructured data (text, images)
Develop data products (e.g., recommendation systems)
🔹 Key Skills
Advanced Python/R
Machine learning
Statistics & probability
Data engineering (sometimes)
🔹 Tools
Python (pandas, scikit-learn, TensorFlow, etc.)
Jupyter Notebook
SQL
Big data tools (Spark, Hadoop)
Git
🔹 Typical Career Path
Data Scientist → Senior Data Scientist → Lead Data Scientist → Chief Data Scientist
- Data Engineer 🔹 Primary Responsibilities
Design, build, and maintain data pipelines
Ensure data is clean, accessible, and available for analysis
Work with databases, APIs, and cloud platforms
Optimize ETL (Extract, Transform, Load) processes
🔹 Key Skills
Strong programming (Python, Java, Scala)
SQL & NoSQL databases
Cloud platforms (AWS, GCP, Azure)
ETL tools (Airflow, dbt)
🔹 Tools
Apache Spark, Kafka
SQL, Redshift, Snowflake
Airflow, dbt
Docker, Kubernetes (sometimes)
🔹 Typical Career Path
Data Engineer → Senior Data Engineer → Data Architect / Platform Engineer → Engineering Manager
- Machine Learning Engineer 🔹 Primary Responsibilities
Productionize machine learning models
Optimize model performance in real-time systems
Work closely with data scientists and engineers
Deploy models via APIs or cloud services
🔹 Key Skills
Machine learning frameworks (TensorFlow, PyTorch)
Software engineering practices (CI/CD, testing)
Data pipelines and APIs
Model monitoring
🔹 Tools
TensorFlow, PyTorch
Docker, Kubernetes
MLflow, SageMaker, Vertex AI
Git, REST APIs
🔹 Typical Career Path
ML Engineer → Senior ML Engineer → AI Architect → Head of AI/ML
- Data Architect 🔹 Primary Responsibilities
Design and manage data architecture and infrastructure
Define data standards, governance, and security
Align data systems with business needs
Collaborate across data teams
🔹 Key Skills
Database management (SQL, NoSQL)
Cloud architecture (AWS, Azure, GCP)
Data modeling and warehousing
Security & compliance
🔹 Tools
ER/Studio, dbt
AWS Redshift, Snowflake
Apache Hive, Presto
Metadata tools (Collibra, Alation)
🔹 Typical Career Path
Data Architect → Principal Architect → Chief Data Officer (CDO)
- Quantitative Analyst (Quant) 🔹 Primary Responsibilities
Use statistical models for financial markets or risk analysis
Build algorithmic trading strategies
Work with large financial datasets
🔹 Key Skills
Advanced statistics & mathematics
Python, R, MATLAB
Financial knowledge
Programming algorithms
🔹 Tools
Python (NumPy, pandas, etc.)
MATLAB, R
Bloomberg, Reuters
SQL
🔹 Typical Career Path
Quant Analyst → Quant Developer → Quant Strategist → Head of Quant Research
- Analytics Engineer 🔹 Primary Responsibilities
Own the transformation layer between raw data and analysis
Create reusable data models (using dbt, SQL)
Work closely with data analysts to deliver clean, well-documented datasets
🔹 Key Skills
SQL (very strong)
dbt, Airflow
Data modeling (Kimball, star/snowflake schemas)
Version control
🔹 Tools
dbt, Airflow
Snowflake, BigQuery
GitHub, Looker
🔹 Typical Career Path
Analytics Engineer → Senior Analytics Engineer → Analytics Architect → Data Platform Lead
- Marketing Analyst / Product Analyst 🔹 Primary Responsibilities
Analyze user/customer behavior and campaign performance
Define KPIs and track conversions, churn, etc.
Provide insights for product/marketing teams
🔹 Key Skills
SQL, Excel
A/B testing & experimentation
Data visualization
Understanding of digital marketing or product lifecycles
🔹 Tools
Google Analytics, Mixpanel, Amplitude
SQL
Tableau/Looker
Excel, Python (basic)
🔹 Typical Career Path
Marketing Analyst → Growth Analyst → Product Analyst → Head of Product Analytics
If you're interested in learning data analytics, I found this course in Pune that looks helpful:https://technogeekscs.com/courses/data-analytics-courses-pune
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