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Posted 3 days ago
Job description
• Amazon S3, AWS Lake Formation, Glue Catalog, Amazon EMR/EC2/Serverless, Spark, Athena
• Angular, Amazon Neptune DB
• Amazon EventBridge, SNS, SQS, API Gateway, AWS Lambda
• Terraform, AWS CloudFormation, IAMFew of our top high level priorities/ outcomes
• Build, Launch and scale DFPaaS (Data Factory Platform as a Service) across Client's Data Product Producers to ensure consistent tooling used to build consistent interoperable high quality data products through DFPaaS
• Strengthen Entitlement capability
• Launch self-serve data subscription and sharing of data products through Data Portal
• Improve data discovery by displaying composite data products only, simplifying catalog organization, content tagging and search on Data Portal.
• Low Latency Solutions
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Software Engineer?
A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.
Q: What is the career path for a Data Software Engineer?
A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.
