{"id":2798654,"url":"https://alion.io/job/mox-bank-data-engineer-data-services","title":"Data Engineer - Data Services","company":{"id":180722,"name":"Mox Bank","domain":"mox.com","url":"https://alion.io/company/mox-bank","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Pinpoint","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hong Kong"],"countries":["HK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache Pulsar","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Boto3","optional":false},{"name":"CI/CD","optional":false},{"name":"CircleCI","optional":false},{"name":"Docker","optional":false},{"name":"Docker Swarm","optional":false},{"name":"Flink","optional":false},{"name":"Hadoop","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kanban","optional":false},{"name":"Kubernetes","optional":false},{"name":"pylint","optional":false},{"name":"pySpark","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"Spinnaker","optional":false},{"name":"Unix","optional":false},{"name":"Vertica","optional":false},{"name":"Alation","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"Databricks","optional":true},{"name":"Datadog","optional":true},{"name":"DynamoDB","optional":true},{"name":"ElasticSearch","optional":true},{"name":"Grafana","optional":true},{"name":"HBase","optional":true},{"name":"Java","optional":true},{"name":"Kibana","optional":true},{"name":"Kotlin","optional":true},{"name":"Logstash","optional":true},{"name":"Lombok","optional":true},{"name":"Looker","optional":true},{"name":"Maven","optional":true},{"name":"MySQL","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Power BI","optional":true},{"name":"Prometheus","optional":true},{"name":"Redis","optional":true},{"name":"Scala","optional":true},{"name":"Superset","optional":true}],"status":"live","first_seen_at":"2026-10-17T01:30:21Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-19T00:27:50Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About Mox\n Mox is built by and for the ones who aspire to live life to the fullest - we call them Generation Mox!\nThe name Mox reflects the endless opportunities we can create, - Mobile eXperience; Money eXperience; Money X (multiplier), eXponential growth, eXploration… it’s all up for us to define together.\nWhy Mox\n Mox helps you grow - your money, your world, your possibilities. We equip you with the financial management tools, information and insights you need to make your dreams, big or small, come true.\nEverything at Mox - from our products, features, to rewards - is designed based on customer research, tailor made for your needs. We care about what customers care about, especially in data security and privacy. Data ethics is core to everyone here at Mox.\nMox rewards you with an array of banking and lifestyle benefits. Who says banking can’t be fun?\nWhat we are looking for?\n\nAs a Data Engineer you'd be working with us to design, maintain, and improve various analytical and operational services and infrastructure which are critical for many other functions within the organization. These include the data lake, operational databases, data pipelines, large-scale batch and real-time data processing systems, a metadata and lineage repository, which all work in concert to provide the company with accurate, timely, and actionable metrics and insights to grow and improve our business using data. You may be collaborating with our data science team to design and implement processes to structure our data schemas and design data models, working with our product teams to integrate new data sources, or pairing with other data engineers to bring to fruition cutting-edge technologies in the data space.\nResponsibilities\n\nHighly relevant: (ideally familiar with at least one of the technologies in most of the below categories)\nGeneral computing concepts and expertise: Unix environments, networking, distributed and cloud computing\nPython frameworks and tools: pip, pytest, boto3, pyspark, pylint, pandas, scikit-learn, keras\nWorkflow scheduling and monitoring tools: Apache Airflow, Luigi, AWS Batch\nColumnar and big data databases: Athena, Redshift, Vertica, Hive/Hadoop\nContainer management and orchestration: Docker, Docker Swarm, ECS, EKS/Kubernetes, Mesos\nCI / CD tools: CircleCI, Jenkins, TravisCI, Spinnaker, AWS CodePipeline\nDistributed messaging and event streaming systems: Kafka, Pulsar, RabbitMQ, Google Pub/Sub\nStreaming data processing frameworks: Spark Streaming, Apache Beam, Apache Flink\nGeneral AWS or Cloud services: Glue, EMR, EC2, ELB, EFS, S3, Lambda, API Gateway, IAM, Cloudwatch\nVersion control: git commands, branching strategies, collaboration etiquette, documentation best practices \nAgile/Lean project methodologies and rituals: Scrum, Kanban\n\nAlso good to have: (familiarity with any of the below concepts or technologies are a plus)\nJVM languages, frameworks and tools: Kotlin, Java, Scala / Maven, Spring, Lombok, Spark, JDK Mission Control\nRDBMS and NoSQL databases: MySQL, PostgreSQL / DynamoDB, Redis, Hbase\nEnterprise BI tools: Tableau, Qlik, Looker, Superset, PowerBI, Quicksight\nData science environments: AWS Sagemaker, Project Jupyter, Databricks\nLog ingestion and monitoring: ELK stack (Elasticsearch, Logstash, Kibana), Datadog, Prometheus, Grafana\nMetadata catalogue and lineage systems: Amundsen, Databook, Apache Atlas, Alation, uMetric\nData privacy and security tools and concepts: Tokenization, Hashing and encryption algorithms, Apache Ranger","description_format":"text","description_chars":3507,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Digital Banks & Neobanks"],"lifecycle":[{"event":"open","at":"2026-10-18T01:30:21Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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