[August Onboard] Data Engineer - Leading HK Digital Bank
Коротко
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!