IT Database Administrator-Level 2 - Experienced (6 - 10 Years)

Job Description

We are seeking a Data Engineer with 3 or more years of hands-on experience in data cleaning, transformation, and analysis using Python. The ideal candidate is comfortable working with large, messy datasets, has exposure to modern data technologies, and brings a strong analytical mindset. Experience with machine learning and LLMs is a strong plus.

Key Responsibilities

• Clean, preprocess, and transform structured and unstructured data using Python


• 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


• 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

Required Skills & Qualifications

• 3+ years of experience as a Data Engineer / Data Analyst


• Strong proficiency in Python for data manipulation and analysis
  
  
  
  • Pandas, NumPy, SciPy
  
  
  
  


• Solid understanding of data cleaning, transformation, and feature engineering


• Experience with SQL (PostgreSQL, MySQL, BigQuery, Snowflake, etc.)


• Familiarity with data visualization tools
  
  
  
  • Matplotlib, Seaborn, Plotly, or Power BI/Tableau
  
  
  
  


• Understanding of statistics and data analysis fundamentals


• Experience working with APIs and external data sources


• Strong problem-solving and communication skills

Modern / Latest Tech Stack (Preferred)

• Python (3.x)


• Pandas, NumPy, Scikit-learn


• Jupyter, 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


• Knowledge of MLOps basics (model versioning, monitoring)