{"id":3484238,"url":"https://alion.io/job/synechron-aws-data-engineer-python-databases-capital-markets-devops","title":"AWS Data Engineer – Python, Databases, Capital Markets & DevOps","company":{"id":5306,"name":"Synechron","domain":"synechron.com","url":"https://alion.io/company/synechron","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":99,"open_postings":22,"ghost_share":0,"stale_share":0.227,"repost_share":0.045,"time_to_fill_p50_days":20,"computed_at":"2026-10-30T05:48:23Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India","Bengaluru, India","Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13000,"max_usd":31000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":53},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Least Privilege","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-29T21:11:48Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-30T15:00:48Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\nSynechron 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.\nThe 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.\nThis 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.\nSoftware Requirements\nRequired Software Skills\nAWS services and cloud infrastructure: Proven experience designing, developing, deploying, and supporting applications and data solutions on AWS.\nPython: Strong professional experience writing clean, efficient, reliable, maintainable, and testable Python code.\nRelational databases: Extensive experience with relational database technologies, including MySQL and PostgreSQL.\nColumnar databases and data formats: Experience with Amazon Redshift and Apache Parquet.\nVector databases: Experience working with vector databases to support project requirements, search, analytics, or data retrieval.\nDatabase design and optimization: Knowledge of schema design, indexing, query optimization, data modeling, and database architecture.\nData engineering: Experience developing data solutions, managing data flows, and working with structured and semi-structured data.\nDevOps: Ability to support cloud deployments, infrastructure activities, CI/CD processes, troubleshooting, and operational reliability.\nCapital markets: Knowledge of capital markets, including Fixed Income instruments and related financial concepts.\nSoftware development practices: Knowledge of software development best practices, design principles, testing, version control, and technical documentation.\nPreferred Software Skills\nAWS certifications relevant to data engineering, cloud architecture, or DevOps.\nExperience with data modeling and data warehousing.\nFamiliarity with DevOps tools and CI/CD pipelines.\nExperience with infrastructure automation and cloud deployment processes.\nUnderstanding of additional financial instruments and capital markets concepts.\nExperience supporting data-intensive applications in financial services or related environments.\nOverall Responsibilities\nDevelop and deploy scalable applications and data solutions on the AWS cloud platform.\nWrite clean, efficient, reliable, and maintainable Python code for data processing, application services, automation, and operational support.\nDesign, implement, maintain, and optimize relational, columnar, and vector databases.\nApply database design and architecture best practices to support performance, scalability, availability, data quality, and maintainability.\nDevelop data and application solutions related to capital markets and Fixed Income instruments.\nBuild and support data models, schemas, data flows, data warehouse structures, and data access processes.\nContribute to DevOps activities, including deployment automation, CI/CD pipelines, infrastructure support, monitoring, and release processes.\nCollaborate with cross-functional teams to define technical requirements, data requirements, solution designs, and delivery priorities.\nTroubleshoot and resolve application, data, database, cloud infrastructure, and deployment issues.\nReview technical designs and recommend improvements to application architecture, database performance, cloud usage, and operational processes.\nApply secure development, access management, data protection, and operational control practices.\nSupport efficient use of AWS compute, storage, database, and data processing resources to promote cost and environmental sustainability.\nPerformance Outcomes and Expectations\nAWS applications and data solutions are delivered in accordance with defined functional, technical, security, and operational requirements.\nPython code meets agreed standards for reliability, maintainability, testability, performance, and documentation.\nDatabase schemas, queries, data models, and storage structures support required performance and scalability.\nRelational, columnar, and vector database solutions are implemented appropriately for project needs.\nData solutions accurately support capital markets and Fixed Income use cases.\nCI/CD and DevOps processes improve deployment consistency, traceability, and operational reliability.\nTechnical issues are investigated systematically, resolved within agreed priorities, and documented for future reference.\nCloud resources are used efficiently through appropriate architecture, monitoring, capacity planning, and optimization.\nTechnical Skills (By Category)\nProgramming Languages\nEssential\nStrong Python programming skills for application development, data processing, automation, testing, and cloud-based solutions.\nAbility to write clean, efficient, reliable, modular, and maintainable code.\nExperience applying software development best practices, design principles, error handling, testing, and documentation.\nAbility to develop code that supports data-intensive applications and capital markets requirements.\nPreferred\nExperience with additional programming or scripting languages used for data engineering, DevOps, or cloud automation.\nExperience developing reusable Python libraries, services, and automation frameworks.\nExperience with asynchronous, distributed, or event-driven application development.\nDatabases and Data Management\nEssential\nExtensive knowledge of relational databases, including MySQL and PostgreSQL.\nExperience with columnar databases, including Amazon Redshift.\nExperience working with Apache Parquet and columnar data storage formats.\nExperience with vector databases.\nKnowledge of database schema design, normalization, partitioning, indexing, and query optimization.\nUnderstanding of data modeling, data quality, data lifecycle management, and data access patterns.\nAbility to select appropriate database technologies based on performance, scalability, query, storage, and project requirements.\nUnderstanding of data structures and data management practices relevant to capital markets and Fixed Income instruments.\nPreferred\nExperience with data warehousing and analytical data models.\nExperience designing data lakes, data warehouses, or hybrid data platforms.\nExperience with data partitioning, compression, archival, and storage optimization.\nExperience with data lineage, metadata management, validation, and reconciliation.\nExperience supporting vector search and retrieval use cases.\nCloud Technologies\nEssential\nProven experience with AWS services and cloud infrastructure.\nExperience developing and deploying scalable applications and data solutions on AWS.\nUnderstanding of cloud computing concepts, including compute, storage, networking, databases, identity, monitoring, and resilience.\nAbility to troubleshoot AWS application, data, infrastructure, and deployment issues.\nUnderstanding of cloud resource management, availability, scalability, and cost considerations.\nPreferred\nAWS certification relevant to data engineering, cloud architecture, or DevOps.\nExperience with infrastructure-as-code and automated environment provisioning.\nExperience with cloud monitoring, alerting, logging, and performance optimization.\nExperience with serverless, containerized, or event-driven AWS architectures.\nExperience applying cloud sustainability practices through resource optimization and efficient data processing.\nFrameworks and Libraries\nEssential\nPython libraries and frameworks relevant to data engineering, application development, database connectivity, testing, and automation.\nLibraries or tools required to work with relational, columnar, and vector databases.\nFrameworks and utilities that support data ingestion, transformation, validation, and processing.\nTechnologies that support the development of capital markets and Fixed Income-related data solutions.\nPreferred\nExperience with data processing and distributed computing frameworks.\nExperience with database migration, schema management, and data quality frameworks.\nExperience with libraries supporting financial data analysis, instrument reference data, pricing data, or risk-related use cases.\nExperience with frameworks for API development, workflow orchestration, and cloud automation.\nDevelopment Tools and Methodologies\nEssential\nKnowledge of software development best practices and design principles.\nExperience with source control, code reviews, testing, release management, and technical documentation.\nAbility to contribute to DevOps activities and cloud deployment processes.\nUnderstanding of CI/CD concepts, automated testing, build processes, deployment controls, and environment management.\nExperience troubleshooting and resolving technical issues across application, database, cloud, and deployment layers.\nAbility to work independently and collaboratively in a team environment.\nPreferred\nFamiliarity with DevOps tools and CI/CD pipelines.\nExperience with automated infrastructure provisioning and configuration management.\nExperience with containerization and orchestration technologies.\nExperience with observability, logging, metrics, alerting, and operational dashboards.\nExperience with Agile development and iterative delivery practices.\nSecurity Protocols\nEssential\nUnderstanding of secure software development practices.\nKnowledge of AWS identity and access management, least-privilege access, authentication, and authorization.\nUnderstanding of database security, encryption, secrets management, and access controls.\nAbility to protect sensitive financial, application, and operational data.\nAwareness of secure coding, vulnerability management, auditability, and secure deployment practices.\nPreferred\nExperience implementing security controls within CI/CD pipelines.\nExperience with cloud security monitoring and configuration assessment.\nFamiliarity with data masking, tokenization, and privacy controls.\nExperience supporting applications subject to financial services, regulatory, or audit requirements.\nExperience Requirements\nMinimum of 7-10 years of professional experience in data engineering, software engineering, cloud engineering, database engineering, DevOps, or related technology roles.\nProven experience with AWS services, cloud infrastructure, Python development, and database engineering.\nExtensive experience with relational databases, including MySQL and PostgreSQL; columnar databases, including Amazon Redshift and Apache Parquet; and vector databases.\nExperience with database schema design, data modeling, query optimization, data warehousing, or related data architecture responsibilities.\nDemonstrated experience developing or supporting solutions related to capital markets, including Fixed Income instruments and related financial concepts.\nExperience with DevOps activities, CI/CD pipelines, deployment processes, troubleshooting, and operational support is preferred.\nIndustry experience in financial services, capital markets, investment technology, or other data-intensive environments is preferred.\nCandidates may qualify through equivalent professional experience, demonstrated technical delivery, relevant certifications, or a combination of data engineering, cloud, database, Python, and capital markets experience.\nThe role requires willingness to work the 12:00 PM to 9:00 PM shift.\nDay-to-Day Activities\nDevelop, test, deploy, and support Python-based data solutions and scalable AWS applications involving relational, columnar, and vector databases.\nCollaborate with cross-functional teams to define technical requirements, data models, capital markets use cases, delivery plans, and 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