Middle Data Engineer

Há 4 dias


Rio de Janeiro Rio de Janeiro, Estado do Rio de Janeiro, Brasil AgileEngine Tempo inteiro
Job Description AgileEngine is a top-ranking provider of software solutions to Fortune 500, Global 500, and Future 50 companies. Listed on Inc. 5000 among the fastest-growing US companies, we are always open to talented software, UX, and data experts in the Americas, Europe, and Asia. If you like a challenging environment where you’re working with the best and are encouraged to learn and experiment daily, there’s no better place — guaranteed :) What you will do Develop applications; engines and integrations; Optimize performance of API’s and integrations with UI’s; Optimize the framework for ML model development and management; Create highly reusable code modules and packages that can be leveraged for many purposes; Design and build efficient data pipelines to integrate data from a variety of sources into Indeed’s Data Warehouse, Machine Learning Pipeline or Applications; Work closely with stakeholders on the data demand side (Sales leadership, Marketing leaders and analysts; and data scientists) and supply side (experts on source systems); Develop and maintain data dictionaries for governance of published data sources as well as improve continuous release and testing processes. Must haves

3 years of experience working with Data Engineer using Python or Java; Ideally a bachelor’s degree in computer science, computer engineering, or an engineering discipline; 3+ years of industry experience in software development and/or data engineering with strong expertise in fast paced and deliver focused environments; Experience delivering data pipelines and managing resulting data stores using managed cloud services (like AWS or Google Cloud Services); Experience developing API’s (REST / GraphQL); integrations with User Interfaces and rules engines – delivering high performance capability e.g. sub second response times; and high concurrency; Experience with modern data pipelines, data streaming, and real time analytics using tools such as Apache Kafka, AWS kinesis, Spark Streaming, ElasticSearch, or similar tools; Experience in columnar relational data stores, NoSQL technologies ( MySQL/Postgresql, Redis, Mongo, ElasticSearch) as well as big data tools such as Google BigQuery, Redshift, Snowflake, as well as knowledge of more traditional warehouses. The benefits of joining us Professional growth Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps. Competitive compensation We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities. A selection of exciting projects Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands. Flextime Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive. Requirements 3 years of experience working with Data Engineer using Python or Java; Ideally a bachelor’s degree in computer science, computer engineering, or an engineering discipline; 3+ years of industry experience in software development and/or data engineering with strong expertise in fast paced and deliver focused environments; Experience delivering data pipelines and managing resulting data stores using managed cloud services (like AWS or Google Cloud Services); Experience developing API’s (REST / GraphQL); integrations with User Interfaces and rules engines – delivering high performance capability e.g. sub second response times; and high concurrency; Experience with modern data pipelines, data streaming, and real time analytics using tools such as Apache Kafka, AWS kinesis, Spark Streaming, ElasticSearch, or similar tools; Experience in columnar relational data stores, NoSQL technologies ( MySQL/Postgresql, Redis, Mongo, ElasticSearch) as well as big data tools such as Google BigQuery, Redshift, Snowflake, as well as knowledge of more traditional warehouses.
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