Lead Data Engineer / Architect at Voltex Electrical

, , Philippines -

Full Time

Start Date

Immediate

Expiry Date

11 Mar, 26

Salary

0.0

Posted On

11 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Architecture, Cloud Data Tools, Azure, Databricks, Snowflake, GCP, AWS, ELT, ETL, SQL, Python, Data Modeling, Data Warehousing, Data Quality, Machine Learning

Industry

electrical;Appliances;and Electronics Manufacturing

Description

Lead Data Engineer / Architect Location: Remote (AU hours) Type: Full-time Team: Data & AI Seniority Level: Staff / Lead Voltex is one of the fastest-growing Direct-to-Consumer (DTC) electrical suppliers in ANZ, with ~$100m turnover and 20% YoY growth. We are profitable, ambitious, and embarking on a massive transformation: shifting from a traditional e-commerce model to an AI-driven, Product-Led Data Ecosystem. We’re mid-flight on a bold migration from on-prem to hybrid-cloud, and we’re looking for a sharp, execution-driven data leader to architect and build our next-generation data stack. You will be the architect behind the "Data Moat" that will define our competitive advantage for years to come. This isn’t just a pipeline-building role. It’s about laying the foundations for analytics, AI, and decision automation across the business. You’ll have significant influence over technical direction, tool selection, and the roadmap for scaling our data capabilities over the next 12–24 months. What You’ll Do Build and Deliver Design and implement modern data pipelines (batch and streaming) to support analytics, reporting, and ML Stand up core cloud data infrastructure (e.g. Azure Data Lake, Databricks, or Fabric) Model business domains and build canonical datasets with clear data contracts Deliver high-impact, high-visibility datasets to analysts, business leads, and ML experiments Collaborate with our growing team of Data Analysts and adjacent IT functions to execute effectively Architect and Scale Define and evolve our cloud-native data platform strategy across Azure, Fabric, or multi-cloud (if needed) Drive best practices for data modeling, data governance, and observability from day one Select technologies and implement scalable architecture patterns (lakehouse, event-driven, etc.) Lay the groundwork for ML readiness, real-time analytics, and MLOps Act as a multiplier: help guide and mentor other technical roles as we expand the team Who You Are You’re a builder at heart—with an eye for architecture and a bias for delivery. You’re looking for a role where you can shape something lasting, but you also want to ship value fast. You’re energized by working cross-functionally and love turning messy reality into elegant data products. You’re assertive without being rigid: confident in your approach, but open to feedback and iteration. You’ll join a growing data environment: we already have Data Analysts in place and expect to reallocate adjacent engineering support (e.g. application DBAs) to complement your work. If you’re looking to put your stamp on something and lead from the front, this is your platform. What We Offer High-autonomy, high-impact role in a business committed to using data strategically Opportunity to define the data platform, practices, and architecture for the entire company Greenfield implementation—real freedom to choose and execute the right solutions, not inherit legacy Strong executive support: you’ll report directly to the CTO and influence data direction company-wide A platform to grow into a leadership role as the data function scales If this sounds like your next chapter, we’d love to talk. What We're Looking For 5+ years in data engineering, ideally with some experience in architecture-level decisions Hands-on experience with cloud data tools (Azure, Databricks, Snowflake, or GCP/AWS equivalents) Proven ability to build robust, scalable ELT/ETL pipelines using tools like Spark, ADF, dbt, Airflow Comfort with both SQL and Python in production environments Solid understanding of data modeling, warehousing, and data quality frameworks Ability to engage both technical and business stakeholders to translate needs into platform capabilities Nice to have Exposure to Delta Lake architectures Experience setting up data governance (e.g., Purview, Unity Catalog) Experience supporting or enabling ML workflows and feature engineering pipelines Competitive salary and benefits package. Opportunity to work with a dynamic and innovative team. Professional growth and development opportunities.

Responsibilities

Design and implement modern data pipelines to support analytics and machine learning. Define and evolve the cloud-native data platform strategy and drive best practices for data governance and observability.