Senior Lead Engineer

Bangalore, Karnataka
Permanent
Full-time

23 days ago

Job RequirementsPerform statistical analysis, identify trends, patterns, and anomalies within datasets using Python libraries such as NumPy, SciPy, and Scikit-learn.Develop and implement predictive models or machine learning algorithms to address specific business problems.Looking for a lead engineer for a data anawith good knowledge in Python Programming ,Experience in working with core data analytics libraries in Python (Pandas, Numpy). He / she should have Experience Web Frameworks & APIs (Flask, FastApi) and containerization , Docker.Experienced and having knowledge in building ETL pipelines, data engineering workflows and Data Visualization (spark, plotly, Dash, SQL)Experience in working with MS Azure Cloud and below Azure Services (Databricks, Data Factory, Azure App Service, Azure Batch Service, CosmosDB, Azure Functions, Azure Datalake)Machine Learning Concepts & Libraries (Time series forecasting , Anomaly Detection, Failure prediction, scikit-learn, statsmodels, PyOD, TensorFlow, PyTorch )Work ExperienceExpert in Python Programming Language

Strong understanding of Python syntax, data structures, OOP, and best practices.
Experience with writing efficient, maintainable, and scalable Python code.

2: Experience in working with core data analytics libraries in Python

Pandas – Data manipulation and analysis
NumPy – Numerical computations
SciPy – Scientific computing, signal processing
Scikit-learn – Classical machine learning algorithms
Statsmodels – Statistical modeling and time series analysis

3: Web Frameworks & APIs

Flask, FastAPI – RESTful APIs and web apps

4: Experience and knowledge in building ETL pipelines and data engineering workflows, including:

Ability to work with structured and unstructured data from various sources.
Understanding of best practices for data quality, reliability, and scalability.
Proficiency in data ingestion, cleansing, transformation, and orchestration.
PySpark, Databricks – distributed data processing frameworks
Azure Data factory -ETL tool
Good SQL knowledge

5: Data Visualization and Dashboards

Plotly, Dash – Interactive visualizations and dashboards
Matplotlib, Seaborn – Static visualizations

6: Experience in working with MS Azure Cloud and below Azure Services:

Azure Databricks
Azure Data Factory
Azure App Service
Azure Batch Service
Azure Cosmos DB
Azure Datalake
Azure DevOps
Azure Functions
Azure Container Registry
Version control (Git)

7: Experience in containerization and Docker, including:

Building, deploying, and managing applications using Docker containers.
Writing and optimizing Docker files for Python and analytics projects.

8: Machine Learning Concepts & Libraries

Time series forecasting
Failure prediction (classification/regression)
Feature engineering from sensor data
Anomaly Detection
Model Evaluation and Deployment
scikit-learn, statsmodels, PyOD, TensorFlow, PyTorch

Quest Global

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