Senior Data Engineer - #1163235

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 accuracy

• Stay 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

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