AWS Data Engineer – Python, Databases, Capital Markets & DevOps

Job Summary

Synechron is seeking an AWS Data Engineer with a 70% focus on data engineering and a 30% focus on DevOps to design, develop, deploy, and support scalable data solutions on AWS.

The role requires strong AWS knowledge, advanced Python development skills, robust database expertise, and an understanding of capital markets, including Fixed Income instruments and related financial concepts. The AWS Data Engineer will work with relational, columnar, and vector databases while supporting cloud infrastructure, CI/CD processes, and reliable application delivery.

This position contributes to business objectives by delivering secure and scalable data solutions, improving database performance, supporting capital markets capabilities, strengthening deployment processes, and enabling reliable access to high-quality data.

Software Requirements

Required Software Skills

• •AWS services and cloud infrastructure: Proven experience designing, developing, deploying, and supporting applications and data solutions on AWS.
• •Python: Strong professional experience writing clean, efficient, reliable, maintainable, and testable Python code.
• •Relational databases: Extensive experience with relational database technologies, including MySQL and PostgreSQL.
• •Columnar databases and data formats: Experience with Amazon Redshift and Apache Parquet.
• •Vector databases: Experience working with vector databases to support project requirements, search, analytics, or data retrieval.
• •Database design and optimization: Knowledge of schema design, indexing, query optimization, data modeling, and database architecture.
• •Data engineering: Experience developing data solutions, managing data flows, and working with structured and semi-structured data.
• •DevOps: Ability to support cloud deployments, infrastructure activities, CI/CD processes, troubleshooting, and operational reliability.
• •Capital markets: Knowledge of capital markets, including Fixed Income instruments and related financial concepts.
• •Software development practices: Knowledge of software development best practices, design principles, testing, version control, and technical documentation.

Preferred Software Skills

• •AWS certifications relevant to data engineering, cloud architecture, or DevOps.
• •Experience with data modeling and data warehousing.
• •Familiarity with DevOps tools and CI/CD pipelines.
• •Experience with infrastructure automation and cloud deployment processes.
• •Understanding of additional financial instruments and capital markets concepts.
• •Experience supporting data-intensive applications in financial services or related environments.

Overall Responsibilities

• •Develop and deploy scalable applications and data solutions on the AWS cloud platform.
• •Write clean, efficient, reliable, and maintainable Python code for data processing, application services, automation, and operational support.
• •Design, implement, maintain, and optimize relational, columnar, and vector databases.
• •Apply database design and architecture best practices to support performance, scalability, availability, data quality, and maintainability.
• •Develop data and application solutions related to capital markets and Fixed Income instruments.
• •Build and support data models, schemas, data flows, data warehouse structures, and data access processes.
• •Contribute to DevOps activities, including deployment automation, CI/CD pipelines, infrastructure support, monitoring, and release processes.
• •Collaborate with cross-functional teams to define technical requirements, data requirements, solution designs, and delivery priorities.
• •Troubleshoot and resolve application, data, database, cloud infrastructure, and deployment issues.
• •Review technical designs and recommend improvements to application architecture, database performance, cloud usage, and operational processes.
• •Apply secure development, access management, data protection, and operational control practices.
• •Support efficient use of AWS compute, storage, database, and data processing resources to promote cost and environmental sustainability.

Performance Outcomes and Expectations

• •AWS applications and data solutions are delivered in accordance with defined functional, technical, security, and operational requirements.
• •Python code meets agreed standards for reliability, maintainability, testability, performance, and documentation.
• •Database schemas, queries, data models, and storage structures support required performance and scalability.
• •Relational, columnar, and vector database solutions are implemented appropriately for project needs.
• •Data solutions accurately support capital markets and Fixed Income use cases.
• •CI/CD and DevOps processes improve deployment consistency, traceability, and operational reliability.
• •Technical issues are investigated systematically, resolved within agreed priorities, and documented for future reference.
• •Cloud resources are used efficiently through appropriate architecture, monitoring, capacity planning, and optimization.

Technical Skills (By Category)

Programming Languages

Essential

• •Strong Python programming skills for application development, data processing, automation, testing, and cloud-based solutions.
• •Ability to write clean, efficient, reliable, modular, and maintainable code.
• •Experience applying software development best practices, design principles, error handling, testing, and documentation.
• •Ability to develop code that supports data-intensive applications and capital markets requirements.

Preferred

• •Experience with additional programming or scripting languages used for data engineering, DevOps, or cloud automation.
• •Experience developing reusable Python libraries, services, and automation frameworks.
• •Experience with asynchronous, distributed, or event-driven application development.

Databases and Data Management

Essential

• •Extensive knowledge of relational databases, including MySQL and PostgreSQL.
• •Experience with columnar databases, including Amazon Redshift.
• •Experience working with Apache Parquet and columnar data storage formats.
• •Experience with vector databases.
• •Knowledge of database schema design, normalization, partitioning, indexing, and query optimization.
• •Understanding of data modeling, data quality, data lifecycle management, and data access patterns.
• •Ability to select appropriate database technologies based on performance, scalability, query, storage, and project requirements.
• •Understanding of data structures and data management practices relevant to capital markets and Fixed Income instruments.

Preferred

• •Experience with data warehousing and analytical data models.
• •Experience designing data lakes, data warehouses, or hybrid data platforms.
• •Experience with data partitioning, compression, archival, and storage optimization.
• •Experience with data lineage, metadata management, validation, and reconciliation.
• •Experience supporting vector search and retrieval use cases.

Cloud Technologies

Essential

• •Proven experience with AWS services and cloud infrastructure.
• •Experience developing and deploying scalable applications and data solutions on AWS.
• •Understanding of cloud computing concepts, including compute, storage, networking, databases, identity, monitoring, and resilience.
• •Ability to troubleshoot AWS application, data, infrastructure, and deployment issues.
• •Understanding of cloud resource management, availability, scalability, and cost considerations.

Preferred

• •AWS certification relevant to data engineering, cloud architecture, or DevOps.
• •Experience with infrastructure-as-code and automated environment provisioning.
• •Experience with cloud monitoring, alerting, logging, and performance optimization.
• •Experience with serverless, containerized, or event-driven AWS architectures.
• •Experience applying cloud sustainability practices through resource optimization and efficient data processing.

Frameworks and Libraries

Essential

Python li