Description

Key Responsibilities

• Collect, preprocess, and analyze large datasets using Python, NumPy, Pandas.
• Develop interactive dashboards and visualizations using Matplotlib, Seaborn, and BI tools (e.g., Tableau, Power BI).
• Write efficient, optimized SQL queries for data extraction, transformation, and reporting.
• Build and maintain data pipelines on AWS or GCP, integrating cloud storage, databases, and analytics services.
• Create and maintain RESTful data services using FastAPI or Django, enabling access to analytics and insights.
• Develop ETL/ELT workflows using tools such as Airflow, Prefect, or dbt.
• Perform exploratory data analysis (EDA), statistical modeling, and hypothesis testing.
• Collaborate with product, engineering, and business teams to define metrics and provide analytical insights.
• Ensure data integrity, documentation, and adherence to data governance standards.
• Work with version control, CI/CD, and containerization for reproducible analysis and deployment.

Required Skills & Qualifications

Core Technical Skills

• Proficiency in Python and key analytics libraries: NumPy, Pandas, Matplotlib, Seaborn.
• Strong SQL skills (joins, aggregation, window functions, query optimization).
• Experience building APIs or internal tools using FastAPI or Django.
• Solid understanding of cloud platforms (AWS, GCP) and services such as:
  • AWS: S3, Redshift, Lambda, Glue
  • GCP: BigQuery, Cloud Storage, Dataflow, Cloud Functions
• Experience with ETL/ELT and workflow orchestration tools (Airflow, Prefect, or dbt).
• Knowledge of data modeling, data warehousing, and pipeline development.
• Understanding of API design, microservices concepts, and application integration.
• Strong data visualization and storytelling skills.

Additional Tools & Tech (Recommended)

• Git & GitHub/GitLab for version control.
• Docker for containerized development environments.
• Jupyter Notebooks and VS Code for data exploration.
• Familiarity with distributed data tools (Spark, Databricks) is a plus.
• Experience with BI platforms such as Tableau, Power BI, Looker.

Preferred Qualifications

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Engineering, or related field.
• Experience working with real-time data (Kafka, Pub/Sub).
• Knowledge of machine learning basics (scikit-learn, feature engineering, model evaluation).
• Experience integrating APIs with frontend dashboards or internal tools.
• Ability to explain technical concepts to non-technical stakeholders clearly.

Key Skills

Education

Any Graduate