Associate Data Engineer

Responsibilities

• Develop data solutions that are flexible, extensible, elastic, secure and reliable at large scale.
• Work with Lead Data Engineer to provide guidance and direction to project teams ensuring compliance with coding standards and best practices.
• Collaborate with Data Governance team to capture and manage meta data, and implement data quality rules.
• Building and managing data pipelines, data products, integrations and promoting production.
• Develop Application Integrations, APIs and Microservices using hybrid cloud architecture.
• Continuously learn and be at the leading edge of Data/Application Integration, Cloud, Containerization, and other industry trends.
• Work with stakeholders including product, data and business teams to assist with data-related technical issues and support their data infrastructure needs.
• Follow Cyber security guidelines and polices to monitor the company's data security and privacy.
• Build and maintain batch data pipelines for structured and semi-structured data
• Support ingestion and preprocessing of unstructured data.
• Implement basic data quality validations (schema checks, null checks).
• Assist in preparing AI-ready datasets for analytics, AI/ML and GenAI use-cases.
• Support implementation of data contracts through schema validation and data checks.

Knowledge, Skills and Abilities

• Practical experience in traditional and cloud data management components (MS SQL, RDS, Athena, or similar).
• Practical experience in metadata driven ingestion framework, building data pipelines and data sets.
• Working-level familiarity with DevOps and Agile methodologies.
• Strong analytical skills.
• Practical understanding of cloud security policies and concepts.
• Exposure to data governance and quality tools.
• Experience with data integration, ETL/ELT orchestration, and application integration using APIs, messaging, or service-based architectures.
• Basic understanding of AI/ML data requirements (training vs inference datasets), structured, semi-structured and unstructured data processing.
• Exposure to streaming concepts, data parsing, text processing.
• Familiarity with data quality and observability concepts.

Education, Experience and Certifications

• Bachelor of Science Degree in MIS or Computer Science/Engineering (or similar) is required.
• Minimum of 2 years of Data Engineering experience.
• Experience developing microservices, serverless components, or distributed data processing solutions.
• Hands-on experience with at least one data integration, data pipelines or application integration platform.
• Practical scripting or programming experience across languages applicable to data engineering workloads.
• Cloud platform certification is preferred.

Physical Requirements

• Willingness to travel if necessary.