Data Engineer/ Data Analyst

We are seeking a Data Engineer/ Data Analyst with expertise in ETL development, data pipeline optimization, and big data processing to drive data-driven decision-making. The ideal candidate will play a crucial role in designing and maintaining scalable data solutions, integrating machine learning models, and optimizing SQL and NoSQL databases for high-performance analytics.

Key Responsibilities:

ETL Development & Data Pipeline Optimization

• Design, build, and optimize ETL/ELT pipelines to transform large-scale structured and unstructured datasets.
• Work with SQL and NoSQL databases (PostgreSQL, MySQL, Elasticsearch) to optimize query performance and ensure efficient data retrieval.
• Automate data quality checks and anomaly detection to ensure consistency across datasets.

Machine Learning & AI Integration

• Collaborate with Data Scientists to build and deploy ML models for anomaly detection, forecasting, and predictive analytics.
• Create feature engineering pipelines to preprocess data for AI/ML applications.
• Deploy AI-driven financial analysis models, integrating LLMs (e.g., Llama 3.3) to automate data extraction and generate insights.

Data Analytics & Business Intelligence

• Develop Power BI dashboards and reports, integrating DAX calculations to track key business metrics and generate actionable insights.
• Automate report generation using Power Automate and enhance data visualization strategies to communicate insights effectively.
• Perform A/B testing, regression analysis, and anomaly detection to support decision-making.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or any Analytics related field.
• Experience with ETL frameworks and proficiency in SQL, Python, and Spark for data manipulation and transformation.
• Hands-on experience with cloud platforms (AWS, GCP, Azure) and data warehouse solutions (Redshift, Snowflake, BigQuery).
• Experience in machine learning model deployment and integrating AI-driven analytics into data pipelines.
• Proficiency in statistical analysis, forecasting, and predictive modeling using Python (Pandas, NumPy, Scikit-learn).
• Familiarity with Power BI, DAX, and Looker Studio for business intelligence and reporting.

Preferred Qualifications & Additional Skills:

Exposure to AutoML, LLM fine-tuning, and MLOps frameworks.

Certifications in Data Analytics & BI / Data Engineer (e.g., Microsoft Certified: Power BI Data Analyst Associate, Google Data Analytics Certificate, Tableau Desktop Specialist).

Proficiency in marketing, operational, or financial analytics, performing deep dives into trends, customer segmentation, and forecasting.