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[August Onboard] Data Engineer - Leading HK Digital Bank

HK3 дн. назад

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Designs and maintains data lake, pipelines, and batch/real-time processing systems for a digital bank; structures schemas and integrates new data sources. · Needs: Proficient in English; substantial experience with Python, workflow scheduling, and big data databases

Описание от работодателя

Our client, a leading digital bank backed by a multinational financial institution is rapidly expanding their team, tackling exciting challenges and delivering top-notch products in small, cross-functional groups. They are currently looking for frontend engineers to onboard in August. Responsibilities: Collaborate with the team to design, maintain, and enhance various analytical and operational services and infrastructure that are vital for numerous functions across the organizatio, include: managing the data lake, operational databases, data pipelines, and large-scale batch and real-time data processing systems, along with a metadata and lineage repository. Work alongside ther data science team to structure data schemas and design data models Partner with product teams to integrate new data sourceseam up with other data engineers to implement cutting-edge technologies in the data domain. Our Ideal Candidate We are looking for: Candidates with substantial experience in some of the following skills and technologies, and a motivation to expand their knowledge on the job. Highly logical, balancing respect for best practices with critical thinking Adaptable to new challenges Capable of independently delivering projects from start to finish Proficient in English communication. Collaboration with teammates and stakeholders is essential, as is the eagerness to be part of a high-performing team that will elevate their careers alongside us. Highly Relevant Skills (familiarity with at least one technology in most categories is preferred): General Computing Expertise: Unix environments, networking, distributed and cloud computing Python Frameworks and Tools: pip, pytest, boto3, pyspark, pylint, pandas, scikit-learn, keras Workflow Scheduling and Monitoring Tools: Apache Airflow, Luigi, AWS Batch Columnar and Big Data Databases: Athena, Redshift, Vertica, Hive/Hadoop Container Management and Orchestration: Docker, Docker Swarm, ECS, EKS/Kubernetes, Mesos CI/CD Tools: CircleCI, Jenkins, TravisCI, Spinnaker, AWS CodePipeline Distributed Messaging and Event Streaming Systems: Kafka, Pulsar, RabbitMQ, Google Pub/Sub Streaming Data Processing Frameworks: Spark Streaming, Apache Beam, Apache Flink General AWS or Cloud Services: Glue, EMR, EC2, ELB, EFS, S3, Lambda, API Gateway, IAM, Cloudwatch Version Control: Git commands, branching strategies, collaboration etiquette, documentation best practices Agile/Lean Methodologies: Scrum, Kanban Additional Skills (familiarity with any of the following is a plus): JVM Languages and Frameworks: Kotlin, Java, Scala / Maven, Spring, Lombok, Spark, JDK Mission Control RDBMS and NoSQL Databases: MySQL, PostgreSQL / DynamoDB, Redis, HBase Enterprise BI Tools: Tableau, Qlik, Looker, Superset, PowerBI, Quicksight Data Science Environments: AWS Sagemaker, Project Jupyter, Databricks Log Ingestion and Monitoring: ELK stack (Elasticsearch, Logstash, Kibana), Datadog, Prometheus, Grafana Metadata Catalog and Lineage Systems: Amundsen, Databook, Apache Atlas, Alation, uMetric Data Privacy and Security Tools and Concepts: Tokenization, hashing and encryption algorithms, Apache Ranger If you feel that this position describes who you are, what you are looking, and you are urgently seeking a new role, we encourage you to apply right away!