Full Time Senior Data Warehouse Engineer Jobs, in LINKTRIX Consultants, Asia Pacific Selangor - Maukerja

We are looking for a Senior Data Warehouse Engineer with strong expertise in data modelling to design, build, and scale modern cloud data platforms. This role focuses on delivering well-structured, high-performance data models that enable analytics, business intelligence, and AI use cases.

You will work closely with solution architects, tech leads, and business stakeholders to translate complex data requirements into scalable data warehouse designs. Beyond engineering, you will play a key role in establishing modelling standards, improving data quality, and guiding the team on best practices.

Key Responsibilities

Data Modelling & Warehouse Design (Core Focus)

Design and implement scalable data models (dimensional, normalized, and hybrid) in Google BigQuery to support analytics and reporting.

Translate business requirements into well-structured data warehouse schemas (fact/dimension, data marts, semantic layers).

Define and enforce data modelling standards, naming conventions, and best practices across projects.

Optimize models for performance, usability, and cost efficiency.

Pipeline & Platform Engineering

Design and build robust ETL/ELT pipelines using GCP services such as Dataflow, Dataproc, Composer (Airflow), Dataform, and Cloud Functions.

Develop batch and streaming pipelines to process structured and semi-structured data.

Ensure seamless integration between ingestion, transformation, and serving layers.

Data Governance & Quality

Implement data quality frameworks, validation rules, and monitoring mechanisms.

Manage metadata, lineage, and documentation to ensure data discoverability and trust.

Apply access control and data security best practices aligned with enterprise requirements.

Performance Optimization & Reliability

Optimize query performance, partitioning, clustering, and storage design.

Troubleshoot pipeline issues and continuously improve system reliability and scalability.

Manage cost-performance trade-offs across data workloads.

Migration & Modernization

Lead data warehouse migration and modernization initiatives (e.g., Oracle, Teradata, on-prem systems to cloud).

Redesign legacy schemas into modern, analytics-friendly models.

Collaboration & Technical Leadership

Partner with analysts, BI developers, and business users to enable self-service analytics.

Mentor junior engineers on data modelling, SQL best practices, and system design.

Conduct design reviews and contribute to architecture decisions.

Requirements

Experience

8+ years of experience in data engineering or data warehousing.

Strong hands-on experience in data modelling and warehouse design.

Minimum 2+ years working with GCP data stack.

Technical Skills

Strong SQL expertise (query optimization, analytical functions, complex joins).

Proficiency in Python for data processing and automation.

Hands-on experience with BigQuery, Dataflow, Dataproc, Composer (Airflow), Dataform.

Deep understanding of: Dimensional modelling (Kimball) Normalized modelling (3NF) Data vault or hybrid modelling approaches

Experience with orchestration, CI/CD, and version control for data pipelines.

Nice to Have

Experience with Azure data stack (Synapse, Data Factory, Databricks).

Exposure to data governance tools and frameworks (e.g., catalog, lineage).

Experience supporting downstream BI tools (Looker, Power BI, Tableau).

Shortlisted candidate will be reached out.