Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

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  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
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  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.
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Job Information

Amazon Sr Data Engineer, Ops Finance Transportation in Hyderabad, India

Description

The Amazon transportation controllership team is looking for a Senior Data Engineer who is data-driven and detail oriented, to partner in expanding our financial data systems to support our global transportation network. You should have excellent business and communication skills to be able to work with business owners and tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate. This person must be strategic and have strong analytical skills, robust interpersonal and influencing skills, strong organizational and project management skills, and is a self-starter. They will need to roll up their sleeves, work both independently and collaboratively across teams, and have a high level of ownership and accountability

Key job responsibilities

  • Architect and develop end to end scalable data infrastructure and data pipelines

  • Develop data products, deploy highly performant solutions, build data infrastructure leveraging AWS services (such as EC2, Redshift, EMR, Lambda, Quicksight etc.)

  • Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.

  • Develop new data models and end to data pipelines.

  • Lead design reviews for other Data Engineers on the team and actively participate in design reviews of related tech products.

  • Provide technical and thought leadership for Data Engineering and Business Intelligence

  • Create and implement Data Governance strategy for mitigating privacy and security risks

  • Design, implement, and support a platform providing secured access to large datasets.

  • Interface with multiple finance and accounting customers, gathering requirements and delivering complete data solutions.

  • Develop ETL pipeline that links various datasets that could serve the analysis objectives in the most efficient way

  • Analyze and solve problems at their root, stepping back to understand the broader context.

  • Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS

A day in the life

Work with the largest dataset in logistics management anywhere in the world to drive business insights, support operations and build analytical solutions for partners which can help drive cost control and decision making. As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models, Gen Ai and ad-hoc data requests. You will be exposed to cutting edge AWS big data technologies.

About the team

Trans Controllership in Finance is one of the most challenging and exciting spaces to work for, with new geographies, new modes and new carriers being launched every day and being required to seamlessly integrate with the Transportation technical systems for automatic Ingestion of Freight invoices, thorough auditing, timely payment and for proper accounting to keep our books clean and accurate.

We are open to hiring candidates to work out of one of the following locations:

Hyderabad, TS, IND

Basic Qualifications

  • 5+ years of data engineering experience

  • Experience with data modeling, warehousing and building ETL pipelines

  • Experience with SQL

  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

  • Experience mentoring team members on best practices

    • Design & Implementation of automated data contract and data quality enforcement mechanisms

    • Expertise at least in 1 data Orchestration tool
    • Working experience in CDK

Preferred Qualifications

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

  • Experience operating large data warehouses

  • Master's degree

  • Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

  • Knowledge of distributed systems as it pertains to data storage and computing

    • Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
    • Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
    • Experience providing technical leadership and mentoring other engineers for best practices on data engineering
    • Strong understanding and experience with DBMS internals.
    • Strong understanding of system performance and scaling
    • Knowledge on LLM and Gen Ai.
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