Senior Data Engineer

6 hours ago

Central Region, Singapore Shinka Labs Full time $120,000 - $180,000 per year

Overview

We are seeking a Senior Data Engineer to join our Forward-Deployed Engineering Team, working full-time with one of our key clients on a long-term Agile engagement.

As a Senior Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, transformations, and curated datasets that power analytics, BI, and machine learning use cases.

You will work closely with product owners, data scientists, BI developers, and business stakeholders to deliver scalable, reliable, and production-grade data solutions.

This is a hands-on, engineering-first role — perfect for someone who thrives on solving complex data problems, optimizing performance, and enabling the broader analytics ecosystem to move faster with confidence.

Key Responsibilities

  • Collaborate with product owners and cross-functional teams to design and implement end-to-end data pipelines supporting analytical and operational workloads.
  • Develop and optimize ETL/ELT processes using Databricks (PySpark, SQL, Delta Live Tables) or similar platforms.
  • Build and maintain curated datasets (Silver / Gold layers) optimized for analytics, BI, and downstream use.
  • Engineer scalable, reusable data models and schemas aligned with business logic and performance needs.
  • Ensure data pipelines are robust, observable, and well-documented, leveraging modern DevOps and CI/CD practices.
  • Implement data quality monitoring, validation, and alerting frameworks.
  • Partner with BI and Data Science teams to enable efficient consumption of data through APIs, views, or shared layers.
  • Optimize data storage, partitioning, and compute costs in cloud environments.
  • (Bonus) Contribute to data infrastructure tooling and automation, including metadata management, lineage, or testing frameworks.

Qualifications & Skills

  • Bachelor's degree in Computer Science, Data Engineering, or a related field.
  • 5–8 years of professional experience in data engineering, preferably in cloud-native environments.
  • Strong proficiency in SQL (analytical queries, optimization, CTEs, views, and data modeling).
  • Hands-on experience with Databricks, Spark, or similar distributed data platforms (e.g., Synapse, BigQuery, Snowflake, Athena).
  • Strong Python development skills for ETL/ELT, data transformation, and automation.
  • Proficiency with Azure cloud services (Data Lake, Functions, Containers, DevOps Pipelines).
  • Solid understanding of data modeling principles (Kimball, dimensional, data vault).
  • Experience implementing CI/CD, Git-based workflows, and Infrastructure as Code (Terraform, ARM templates).
  • Familiarity with monitoring and observability tools for data pipelines.
  • Excellent problem-solving, communication, and stakeholder collaboration skills.

What We Offer

  • Long-term, embedded client engagements in Agile, product-driven teams.
  • The opportunity to own the full lifecycle of data engineering delivery — from ingestion to production.
  • Exposure to modern data stacks and cloud-native engineering.
  • A collaborative, engineering-led culture that values craft, autonomy, and impact.

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