Senior Data Engineer

Job Description

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

Role Overview (Non-Exhaustive)

This role focuses on extracting insights and value from complex datasets using statistical analysis, machine learning, and data visualization techniques.

You will collaborate with business stakeholders to understand challenges, develop predictive and prescriptive models, and communicate findings to support data-driven decision-making.

Close collaboration with data engineers and AI teams is required 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 build machine learning models
• Implement data quality checks, validation rules, and monitoring processes
• Automate data workflows to ensure timely data availability
• Work with cloud platforms such as Azure, AWS, or GCP

Additional Responsibilities (Non-Exhaustive)

• Analyze large datasets to identify trends, patterns, and insights
• Develop, train, and validate predictive and classification models
• Evaluate and select appropriate AI foundation models where applicable
• Design experiments and conduct hypothesis testing
• Collaborate with data engineers to optimize data for analysis
• Translate findings into actionable business recommendations
• Present insights using visual storytelling techniques
• Monitor and maintain production models to ensure accuracyStay updated on emerging data science tools and best practices

Quality Testing Responsibilities

• Develop and execute data validation and quality test cases
• Perform unit and integration testing for data pipelines
• Monitor data accuracy, completeness, and consistency
• Identify and resolve data anomalies with engineering teams
• Document test results and maintain logs

Requirements

Compulsory Requirements

• Strong machine learning experience
• Proficiency in Python or R
• Hands-on experience with SQL and data manipulation
• Strong knowledge of statistics, machine learning algorithms, and data mining techniques
• Experience in data preprocessing, feature engineering, and model validation
• Ability to perform exploratory data analysis (EDA)
• Experience building, training, and validating predictive or classification models
• Ability to communicate technical concepts to non-technical stakeholders

Preferred Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• 3-5 years of relevant experience in data engineering, data science, or similar roles
• Experience with cloud platforms (Azure, AWS, GCP) and related tools
• Experience with data engineering tools (Azure Data Factory, AWS Glue, BigQuery)
• Familiarity with big data technologies (Spark, Hadoop)
• Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn)
• Knowledge of cloud ML platforms (SageMaker, Azure ML, GCP AI Platform)
• Understanding of experimental design and A/B testing
• Experience with orchestration tools (Airflow, ADF, Glue)
• Familiarity with DevOps practices and CI/CD for data pipelines
• Knowledge of containerization tools (Docker, Kubernetes)
• Experience with data warehousing platforms (Snowflake, Redshift, BigQuery)
• Exposure to monitoring, logging, and alerting for data workflows

We regret to inform that only shortlisted candidates will be notified.