Senior Data Engineer

Role Description

Responsible for extracting insights and value from complex datasets by applying statistical analysis, machine learning, and data visualization techniques. The role involves collaborating with business stakeholders to understand problems, developing predictive and prescriptive models, and communicating findings to support data-driven decision-making. Data Scientists work closely with data engineers and AI teams to operationalize models and ensure actionable outcomes.

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.
• Develop and execute data validation and data quality test cases.
• Perform unit and integration testing for data pipelines.
• Proficient in programming languages such as Python or R

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
• 3–5 years of experience in data engineering, data science, or related domains.
• Hands-on experience with SQL, Python, and distributed data systems.
• Knowledge of machine learning techniques and statistical analysis.
• Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
• Familiarity with DevOps practices and CI/CD for data pipelines.