MODEC

Overview of job

Overall Job Purpose

• The Senior Data Engineer will be part of Data Engineering team which is creating, maintaining, scaling and improving the enterprise data platform providing the data for AI/Data Science solutions, applications/tools, and other digital use cases.

Core Responsibilities

• Design, develop, and maintain robust, scalable and sustainable data products and build & optimize data pipeline and infrastructure.
• Collaborate with stakeholders to understand their data requirements and translate them into technical solutions.
• Identify and implement data quality monitoring and validation processes to ensure data integrity.
• Implement data quality frameworks and ensure data governance best practices, including data lineage, data documentation, and data security.
• Build out the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Synapse, ADF, Spark, Kafka, or similar technologies.
• Work closely with Data Analysts and Data Architect to support their data needs and enable advanced analytics and machine learning initiatives.
• Contribute to the development of the organization's data strategy, including evaluating new technologies, tools, and frameworks to enhance the data engineering ecosystem.

Educational Qualification & Experience:

• BA/BS degree in Computer Science, Computer Engineering, Electrical Engineering or related technical field
• 4-8 years to total IT experience preferably in field of data engineering
• 4+ years' experience with Azure services including IAM, Synapse, DataLake, SQL Server, ADF etc.
• 2+ years' experience in creating and deploying docker containers on Kubernetes.
• 2+ years' experience in supporting development teams on Kubernetes best practices, troubleshooting, and performance optimization.
• 2+ years' experience with CI/CD pipelines toll such as Jenkins and GitHub Actions
• 2+ years' experience with Synapse data warehousing and data lake solutions
• Strong programming skill in Python, PySpark and SQL
• 4+ years of experience in scripting and automation using languages such as Bash, Python, or Go2+ years of experience with infrastructure-as-code tools such as Terraform, Ansible, or CloudFormation and containerization technologies (e.g., Docker, Kubernetes).
• Knowledge of Agile methodologies and software development lifecycle processes
• Proven experience in designing and implementing large-scale data solutions, including data pipelines and ETL processes on Azure.

Required Knowledge:

• Troubleshoot and resolve data-related issues, performance bottlenecks, and scalability challenges on Azure
• Solid understanding of DevOps principles and experience with infrastructure automation using tools like Terraform or CloudFormation.
• Hands-on experience with cloud platforms - Azure, and related services (e.g., Synapse, Data Lake, etc.).
• Understandings of data warehousing concepts and best practices
• Work closely with stakeholders to understand business requirements and translate them into data solution designs.
• Strong understanding of data architecture principles, data modelling techniques, and data integration patterns.

Language(s) and Software:

• Excellent in English (speaking and writing)

Key Behaviors:
Soft Skills (Professional) List maximum 3
a) Excellent communication skills with a strong technology focus.
b) Excellent analytical abilities.
c) Problem Solving – providing sustainable solutions.