Job Description
Description
Key Responsibilities:
- Clean, preprocess, and transform structured and unstructured data using Python
- Data Engineer will perform exploratory data analysis (EDA) to uncover insights and trends
- Build reusable data pipelines and feature engineering workflows
- Work with SQL and/or cloud-based data warehouses to extract and prepare data
- Collaborate with stakeholders to translate business problems into data-driven solutions
- Develop and maintain analytical models and dashboards
- As a Data Engineer, you will apply basic to intermediate machine learning techniques where applicable
- Experiment with and support LLM-based solutions (prompting, embeddings, APIs) as needed
- Ensure data quality, reliability, and documentation
Requirements
- 3+ years of experience as a Data Engineer/Data Analyst
- Experience with SQL (PostgreSQL, MySQL, Big Query, Snowflake, etc.)
- Experience working with APIs and external data sources
- Solid understanding of data cleaning, transformation, and feature engineering
- Familiarity with data visualization tools; Matplotlib, Seaborn, Plotly, or Power BI/Tableau
- Understanding of statistics and data analysis fundamentals
- Strong proficiency in Python for data manipulation and analysis; Pandas, NumPy, SciPy
- Strong problem-solving and communication skills
Modern/Latest Tech Stack (Preferred):
- Python (3.x)
- Pandas, NumPy, Scikit-learn
- Jupiter, VS Code
- Git/GitHub
- Cloud platforms: AWS/Azure/GCP
- Data tools: Airflow, dbt, Spark (basic exposure)
- Containerization: Docker (nice to have)
Good to Have:
- Hands-on experience with Machine Learning models; Regression, classification, clustering, time series
- Exposure to LLMs and Generative AI; OpenAI/Azure OpenAI APIs; Prompt engineering; Embeddings, vector databases (FAISS, Pinecone, Chroma)
- Experience with NLP or text analytics
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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