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 libraries and frameworks relevant to data engineering application development database connectivity testing and automation.
• Libraries or tools required to work with relational columnar and vector databases.
• Frameworks and utilities that support data ingestion transformation validation and processing.
• Technologies that support the development of capital markets and Fixed Income-related data solutions.

Preferred

• Experience with data processing and distributed computing frameworks.
• Experience with database migration schema management and data quality frameworks.
• Experience with libraries supporting financial data analysis instrument reference data pricing data or risk-related use cases.
• Experience with frameworks for API development workflow orchestration and cloud automation.

Development Tools and Methodologies

Essential

• Knowledge of software development best practices and design principles.
• Experience with source control code reviews testing release management and technical documentation.
• Ability to contribute to DevOps activities and cloud deployment processes.
• Understanding of CI/CD concepts automated testing build processes deployment controls and environment management.
• Experience troubleshooting and resolving technical issues across application database cloud and deployment layers.
• Ability to work independently and collaboratively in a team environment.

Preferred

• Familiarity with DevOps tools and CI/CD pipelines.
• Experience with automated infrastructure provisioning and configuration management.
• Experience with containerization and orchestration technologies.
• Experience with observability logging metrics alerting and operational dashboards.
• Experience with Agile development and iterative delivery practices.

Security Protocols

Essential

• Understanding of secure software development practices.
• Knowledge of AWS identity and access management least-privilege access authentication and authorization.
• Understanding of database security encryption secrets management and access controls.
• Ability to protect sensitive financial application and operational data.
• Awareness of secure coding vulnerability management auditability and secure deployment practices.

Preferred

• Experience implementing security controls within CI/CD pipelines.
• Experience with cloud security monitoring and configuration assessment.
• Familiarity with data masking tokenization and privacy controls.
• Experience supporting applications subject to financial services regulatory or audit requirements.

Experience Requirements

• Minimum of 710 years of professional experience in data engineering software engineering cloud engineering database engineering DevOps or related technology roles.
• Proven experience with AWS services cloud infrastructure Python development and database engineering.
• Extensive experience with relational databases including MySQL and PostgreSQL; columnar databases including Amazon Redshift and Apache Parquet; and vector databases.
• Experience with database schema design data modeling query optimization data warehousing or related data architecture responsibilities.
• Demonstrated experience developing or supporting solutions related to capital markets including Fixed Income instruments and related financial concepts.
• Experience with DevOps activities CI/CD pipelines deployment processes troubleshooting and operational support is preferred.
• Industry experience in financial services capital markets investment technology or other data-intensive environments is preferred.
• Candidates may qualify through equivalent professional experience demonstrated technical delivery relevant certifications or a combination of data engineering cloud database Python and capital markets experience.
• The role requires willingness to work the 12:00 PM to 9:00 PM shift.

Day-to-Day Activities

• Develop test deploy and support Python-based data solutions and scalable AWS applications involving relational columnar and vector databases.
• Collaborate with cross-functional teams to define technical requirements data models capital markets use cases delivery plans and operational priorities.
• Review database performance cloud infrastructure CI/CD processes application behavior and production issues while implementing improvements and resolving defects.
• Make technical decisions within approved standards regarding data architecture schema design database optimization AWS deployment DevOps practices and solution maintainability.

Qualifications

• Bachelor of Engineering or equivalent qualification in Computer Science Information Technology Engineering or a related field; equivalent relevant professional experience may be considered.
• Minimum of 710 years of experience in data engineering software engineering cloud engineering database engineering DevOps or a related field.
• AWS certifications are preferred but not required where equivalent practical AWS experience is demonstrated.
• Training or practical experience in Python AWS database architecture data modeling data warehousing DevOps CI/CD and capital markets is preferred.
• Continuous professional development is expected through relevant certifications technical training cloud learning database education and knowledge of evolving capital markets technology practices.

Professional Competencies

• Applies structured analysis and problem-solving to investigate data database Python AWS application infrastructure and deployment issues.
• Works effectively with cross-functional teams contributes technical knowledge and supports shared delivery goals across data engineering and DevOps activities.
• Communicates technical requirements database designs project risks financial concepts issues and recommendations clearly to technical and non-technical stakeholders.
• Adapts to changing AWS services data architectures database technologies capital markets requirements delivery priorities and operational needs.
• Identifies practical improvements in data architecture database performance automation deployment reliability resource usage and solution sustainability.
• Organizes work across development testing troubleshooting documentation production support and delivery commitments while prioritizing tasks according to business impact.

SYNECHRONS DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.

All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.

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