Role Overview :

The Data Engineer / Data Scientist will be responsible for designing, developing, and maintaining data pipelines, performing data analysis, building predictive models, and ensuring data quality across platforms and operations.

Key Responsibilities :

- Design, build, and optimize scalable data pipelines and ETL processes.

- Develop and maintain data models, data marts, and analytical datasets.

- Collaborate with cross-functional teams to gather requirements and deliver data-driven solutions.

- Perform exploratory data analysis (EDA) and create machine learning models as required.

- Implement data quality checks, validation rules, and monitoring processes.

- Automate data workflows and ensure timely availability of data.

- Work with cloud platforms such as Azure, AWS, or GCP for data engineering activities.

Technical Skills :

- Proficient in programming languages such as Python or R.

- Expertise in statistics, machine learning algorithms, and data mining techniques.

- Experience with data preprocessing, feature engineering, and model validation.

- Skilled in data visualization tools and libraries (Tableau, Power BI, Matplotlib, Seaborn).

- Familiarity with big data platforms (Spark, Hadoop) and SQL databases.

- Knowledge of cloud-based ML platforms (AWS SageMaker, Azure ML, GCP AI Platform).

- Understanding of experimental design and A/B Testing.

Quality Testing Responsibilities :

- Develop and execute data validation and data quality test cases.

- Perform unit and integration testing for data pipelines.

- Monitor data accuracy, completeness, and consistency across systems.

- Identify data anomalies and work with engineering teams to resolve issues.

Must Have :

- SQL, Python, Data Science, Azure, AWS, Spark