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Middle Data Engineer
2 meses atrás
3+ years of experience working as a 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 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 as a 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 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.
