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Certifications in AWS DevOps, AWS RDS/DMS, data engineering, data science, automation, or database technologies a plus. Set up best practice standards for data engineering in alignment with Bank's defined Enterprise and data architecture.
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Familiarity with data streaming technologies such as Kafka, Kinesis, spark streaming, etc. We use cloud-native architectures and modern data engineering practices to help data engineers, data scientists, and business analysts realize their full potential.
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Preferred Tools: Data bricks, Snowflake, Apache Airflow, Microsoft Azure Data Factory, Kafka, Power BI, SSAS. Working experience of scripting, data engineering and analytics (SQL, Python, devops CI/CD pipelines, Airflow/ADF, Machine Learning (good to have.
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Experience with modern data engineering tools such as Talend, DBT, Databricks, Snowflake and data visualization tools such as PowerBI, Tableau, ThoughtSpot. Background working in data streaming and data capture technologies such as FiveTran, ADF, and Kafka and various relational, columnar, graph and vector databases.
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Develop, train, and apply data engineering techniques to automate manual processes, and solve challenging business problems. ideally 3+ years of hand-on experience in distributed processing using Databricks, Apache Spark, Kafka & leveraging Airflow scheduler/executor framework.
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Drive the adoption of best practices in data engineering, including continuous integration and delivery (CI/CD) pipelines using tools like GitHub, Jenkins, and UCD. - Proven experience in data engineering and leadership, with a strong portfolio of successful data pipeline creation and management.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Experience with Power BI, Tableau or other Reporting and Data Visualization toolsFamiliarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code toolsAbility to work from our Manhattan, NY office at least twice a weekEducation/Experience:Bachelor’s degree in MIS, CS, Engineering or equivalent field.
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The successful candidate will have a solid foundation in data engineering principles, substantial experience with Databricks, and a proven track record of implementing robust data solutions.
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Certifications in AWS DevOps, AWS RDS/DMS, data engineering, data science, automation, or database technologies are a plus. PLEASE NOTE, THIS IS NOT A DEVOPS POSITION. It is a Data Engineering role within RDS/AWS.
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The ideal candidate will have a strong background in data engineering and be proficient in using the ELK (elastic, kibana, logstash) stack and Databricks for data processing and analytics.
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Hands on experience in the following environments is preferred: Java Stack, Automation (BPM, CMMN, RPA, OCR, ML, Drools), CI/CD (Jenkins, Gitlabs), Cloud Native (Envoy, docker, Kubernates, OpenShift, Etcd, Consul, gRPC, ProtoBuf), DB's ( Postgres, Oracle, CouchBase, Cassandra, Redis, Elastic Stack), Performance engineering (CPU and heapdump analysis, Dynatrace), Message broker (Kafka, Rabbit MQ.
$170,000 - $255,000 a yearFull-timeExpandApply NowActive JobUpdated 16 days ago - UpvoteDownvoteShare Job
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Harness the power of streaming platforms like message queue and Kafka to enable real-time data processing and analysis, empowering the bank to make data-driven decisions and deliver personalized customer experiences.
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You have experience with large scale data processing technologies (e.g. Spark, Flink, Kafka, Airflow, YARN/Hadoop) You have experience in backend engineering, data infrastructure, search infrastructure or natural language processing/machine learning.
$130,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Experience with at least 3 of the technologies/tools mentioned here: HAProxy, Kafka, Big Data/ Hadoop, Presto, Spark, Airflow, Pinot, Druid, Opensearch, Gcp, Data Proc. Experience scaling production systems running Big Data tools like Spark, Hadoop, Apache Druid, Looker.
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Skills Required: Requires experience in the following: Agile SDLC; Microservices Architecture; Apache Kafka; Java; J2EE; Jenkins; Spring; Spring Boot; Spring AOP; Spring Data JPA; Hibernate; HTML; ReactJs; JavaScript; NodeJs; REST; SOAP; JSON; GIT; JUnit; Mockito; AWS Cloud; Datadog; Python; PySpark; Karate Framework; Docker; and NoSQL Database solutions platform and SQL databases.
$169,229 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago
data engineering kafka jobs in New York, NY
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