{"id":2198567,"url":"https://alion.io/job/thinkwiseglobal-snowflake-aws-engineer","title":"Snowflake / AWS Engineer","company":{"id":3806720,"name":"Thinkwiseglobal","domain":"thinkwiseglobal.com","url":"https://alion.io/company/thinkwiseglobal","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"Incident Management","optional":false},{"name":"Liquibase","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Java","optional":true}],"status":"live","first_seen_at":"2026-10-09T19:41:01Z","employer_posted_date":null,"last_verified_at":"2026-10-09T19:41:01Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Snowflake AWS - Engineer \nJob Location: Hyderabad, Indore and Ahmedabad (India)\nExp - 2-4 years experience\n\nRole Overview\nWe are seeking a skilled Snowflake Data Engineer to join our team. The ideal candidate will be responsible for designing, developing, deploying, and supporting enterprise data solutions on the Snowflake platform. This role involves building scalable data pipelines, developing metadata-driven frameworks, automating database deployments, and supporting production environments. The successful candidate will possess strong troubleshooting skills, be comfortable working across both application and database administration domains, and consistently produce well-documented, maintainable solutions.\n\nKey Responsibilities\nSnowflake Engineering & Development\nDesign, develop, and maintain robust data solutions using Snowflake.\nDevelop and support database objects including tables, views, streams, tasks, stored procedures, and dynamic SQL frameworks.\nBuild scalable and performant ETL/ELT pipelines for data integration and analytics workloads.\nOptimize Snowflake query performance, storage utilization, and compute efficiency.\nImplement metadata-driven and configuration-based data processing frameworks.\nDatabase Administration & Scripting\nDevelop, support, and maintain database administration scripts for operational and support activities.\nCreate automation scripts for database monitoring, housekeeping, deployments, validations, and health checks.\nAssist with Snowflake platform administration activities, including role management, access controls, warehouse management, and object security.\nSupport operational automation across development, test, and production environments.\nSupport Amazon Aurora PostgreSQL operational activities, including connectivity validation, performance troubleshooting, access coordination, and environment support.\nDatabase Deployment & Release Management\nUtilize Liquibase for source-controlled database deployments and schema migrations.\nDevelop and maintain deployment scripts and release automation processes.\nEnsure database changes are properly version-controlled, tested, and promoted through environments.\nData Engineering & Operational Support\nDevelop efficient data ingestion, transformation, and validation processes.\nDesign, develop, and support AWS Glue jobs and workflows for data ingestion, transformation, cataloging, and orchestration across cloud and enterprise data platforms.\nWork with Amazon S3 for data landing, staging, archival, file organization, access patterns, and integration with Snowflake and AWS Glue pipelines.\nSupport AWS Database Migration Service (AWS DMS) tasks for data replication, migration, validation, monitoring, and issue resolution across source and target platforms.\nTroubleshoot and resolve issues related to data pipelines, database performance, and application integrations.\nPerform root cause analysis and implement corrective actions for recurring issues.\nMonitor data loads, data quality processes, and platform performance to ensure reliability and\navailability.\nSupport production incident management and operational escalations.\nSystem Integration & DevOps\nSupport CI/CD processes for database and data engineering solutions.\nUtilize GitHub for source code management, version control, and collaboration.\nCollaborate with application development, infrastructure, and data teams to deliver integrated enterprise solutions.\nIntegrate Snowflake solutions with AWS services, including AWS Glue, Amazon Aurora PostgreSQL, Amazon S3, and AWS DMS, to support scalable enterprise data processing and interoperability.\nParticipate in code reviews, deployment reviews, and technical design discussions.\n\nRequired Skills & Experience\nSnowflake Engineer 4 years experience and at least 2 years of relevant data engineering experience, including hands-on work with cloud data platforms and production data environments.\nStrong hands-on working experience with Snowflake development and administration.\nProficiency in writing and optimizing complex SQL queries and Snowflake stored procedures.\nHands-on proficiency with AWS Glue for ETL development, workflow orchestration, job monitoring, and troubleshooting.\nExperience developing database and application support scripts.\nExperience working with Amazon Aurora PostgreSQL, including SQL development, integration support, operational troubleshooting, and performance analysis.\nExperience working with Amazon S3 for storage, ingestion, staging, and integration with cloud-native data pipelines.\nExperience with AWS DMS for database migration, change data capture, replication monitoring, and troubleshooting.\nHands-on experience with Liquibase for database deployment and schema version management.\nStrong troubleshooting, analytical, and problem-solving skills.\nExperience supporting production data warehouse or data platform environments.\nAbility to develop maintainable, reusable, and well-documented code.\nExperience with source control systems such as GitHub.\nExcellent verbal and written communication skills.\nStrong attention to detail and commitment to operational excellence. .\n\nEducation\nBachelor's or master's degree in computer science, Engineering or a related field (or 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