Senior Data Platform Engineer — Databricks & AWS

Finlync Company Limited; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Finlync Company Limited is seeking a Senior Data Engineer to design, build and optimize scalable data platforms on Databricks and AWS. You will shape data models, governance and lakehouse architectures, while delivering reliable ETL/ELT pipelines and production-grade data solutions for complex enterprise needs.

Collaborate with software engineers, data analysts and DevOps to drive standards, CI/CD, and platform-wide reliability.

Qualifications

• 5+ years of experience in Data Engineering, Data Platform Engineering, or a similar role.
• Strong hands-on experience with Databricks and Apache Spark / PySpark.
• Strong SQL and Python development skills.
• Experience building production-grade ETL/ELT pipelines at scale.
• Strong understanding of Delta Lake and Lakehouse architecture.
• Good understanding of data modelling and data warehouse concepts.
• Experience working with AWS data services, particularly S3, IAM, Glue.
• Good understanding of distributed data processing and its performance considerations.
• Experience with orchestration, scheduling, dependency management, monitoring, and failure recovery.
• Understanding of data quality, lineage, governance, and access‑control concepts.
• Experience implementing CI/CD and software engineering practices for data pipelines.
• Ability to independently analyse technical problems and propose scalable solutions.
• Ability to explain architectural decisions and their trade‑offs clearly.

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines using Databricks.
• Develop reliable ETL/ELT pipelines for ingesting data from databases, APIs, Kafka/event streams, files, and other enterprise systems.
• Design and maintain data lake / lakehouse architecture on AWS and Databricks.
• Build and optimise Bronze, Silver, and Gold data layers using Delta Lake and Medallion Architecture principles.
• Work with stakeholders and engineering teams to define appropriate data models, schemas, and data contracts.
• Participate in architectural discussions and help define standards for data ingestion, storage, modelling, streaming architecture, data quality, governance, security and access control, scalability and performance.
• Design solutions that balance performance, maintainability, cost, and operational complexity.
• Build reusable data frameworks, libraries, and platform components rather than one-off pipelines.
• Improve pipeline performance through partitioning, clustering, query optimisation, caching, and efficient Spark processing.
• Implement monitoring, alerting, logging, lineage, and data quality checks across data pipelines.
• Troubleshoot production data issues and perform root-cause analysis.
• Ensure data platforms are resilient, observable, and recoverable.
• Work closely with Software Engineers, Data Analysts, BI teams, DevOps/Platform Engineers, and Solution Architects.
• Contribute to technical design reviews and provide guidance to other Data Engineers.
• Support CI/CD, infrastructure automation, testing, and release practices for data workloads.
• Continuously evaluate improvements to the data platform, engineering standards, and architecture.

Skills

Databricks

Spark

PySpark

SQL

Python

ETL pipelines

Delta Lake

Lakehouse

AWS

Data modelling

Data governance

CI/CD practices

Tools

S3

IAM

Glue

Kafka

Databricks

Job description

Finlync Company Limited is seeking a Senior Data Engineer to design, build and optimize scalable data platforms on Databricks and AWS. You will shape data models, governance and lakehouse architectures, while delivering reliable ETL/ELT pipelines and production-grade data solutions for complex enterprise needs.

Collaborate with software engineers, data analysts and DevOps to drive standards, CI/CD, and platform-wide reliability.