Data Engineer – Build Scalable Data Pipelines

About the role

As a Data Engineer at Salmon, you will design and own data pipelines and lakehouse architecture that transform raw data into reliable inputs for products used by millions across Southeast Asia.

Key responsibilities

• Design and run batch and streaming pipelines on Databricks and Apache Spark over AWS, ingesting from databases, APIs, and event streams.
• Shape lakehouse architecture on S3 and Delta Lake, implementing medallion (Bronze/Silver/Gold) layering and storage optimization.
• Own projects end‑to‑end, from stakeholder alignment and design review through implementation, launch, and ongoing support.
• Build self‑service data solutions that scale as new sources and use cases are added.
• Maintain fault‑tolerant, cost‑optimized ETL/ELT pipelines and optimize Spark jobs (cluster sizing, caching, joins, shuffles, partitioning, Parquet/Delta formats).

Required profile

• Hands‑on experience with Databricks and strong proficiency in Apache Spark (PySpark or Scala).
• Strong Python programming for data engineering, plus SQL and Spark SQL for transformations.
• Experience with Delta Lake and lakehouse architectures, including performance optimization.
• Proven ability to own projects end‑to‑end, gather feedback, and deliver scalable, maintainable solutions.

Required skills

• Databricks
• Apache Spark
• PySpark
• Scala
• Python
• SQL
• Spark SQL
• Delta Lake
• AWS (S3)
• Unity Catalog
• Git
• Terraform (optional)
• Ansible (optional)

What we offer

• Ownership and flexibility in a fast‑growing fintech.
• Stock option plan with four‑year vesting.
• Hybrid‑first model with fully remote work available for eligible roles.
• Company‑provided tools, equipment, and office in Bonifacio Global City, Manila.
• Medical insurance support for you and your family, plus generous vacation and parental leave.