Data Engineering & Backend Development

• Proficient in AWS cloud services, including: ○ AWS Glue, Redshift, Athena, Lambda, S3, RDS, DynamoDB, Step Functions, IAM, CloudWatch.
• Experience with AWS Kinesis, EventBridge, and Apache Kafka for real-time data streaming.
• Strong experience in API development using FastAPI, Flask, Django, or Express.js.

Database Management:

• Expertise in SQL (PostgreSQL, MySQL, Snowflake, BigQuery) and NoSQL (MongoDB, Firebase).
• Experience optimizing data lakes, data warehouses, and OLAP databases.
• ETL/ELT & Data Pipeline Orchestration: ○ Hands-on experience with Apache Airflow, Prefect, dbt (Data Build Tool), Luigi.
• Proficiency in data pipeline automation and workflow scheduling.

Data Analytics & AI-Powered Visualization

• Proficiency in Tableau, Infogram, Power BI, Google Data Studio, and Superset.
• Hands-on experience with D3.js, Chart.js, Highcharts, ECharts for HTML-based data visualization.
• Experience using AI for predictive analytics, anomaly detection, and sentiment analysis.
• Strong Python skills (Pandas, NumPy, Matplotlib, Seaborn, Plotly, Dash) for exploratory data analysis.
• Experience with AI tools for auto-generated dashboards and AI-powered insights (ChatGPT API, OpenAI embeddings, NLP models, LlamaIndex, LangChain).
• Familiarity with machine learning models (Scikit-learn, TensorFlow, PyTorch) for forecasting and predictive analytics. Preferred Qualifications:
• Experience in real estate, financial data analytics, or SaaS platforms.
• Familiarity with cloud-based AI analytics tools such as AWS QuickSight, Google Vertex AI, and Azure AI services.
• Understanding of business intelligence (BI), KPI tracking, and A/B testing for data-driven decision-making.
• Experience in automating AI-powered financial reports and marketing insights.