Data Engineer
Share
Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Who We Are
We are a global technology consultancy with a trademarked AI-first engineering approach for accelerating the delivery of digital products and revolutionizing platform modernization. We do the right thing and we do it right. Were proud to be a World Economic Forum New Champion and a B Corp-certified company.
About Gen-e2
While the market is still largely AI-augmenting delivery we have reinvented the SDLC to be AI First. Our approach is a game-changer in productivity and quality:
- We now generate 95% of the entire product code documentation infrastructure as code and even design with GitHub Copilot.
- The quality consistently exceeds the output of our best traditional engineering teams.
- A product repository houses all product artefacts giving AI full project context for higher-quality generation.
- A library of rules and prompts defines coding standards design principles and security guidelines ensuring enterprise-grade quality and scalability.
With Gen-e2 we deliver end-to-end products 23 faster than traditional approaches while raising the bar for engineering excellence.
YOUR ROLE:
We are seeking a Data Engineer to build and operate enterprise-scale data pipelines primarily on Microsoft Azure with exposure to AWS and GCP as a plus. This role supports critical business domains including Financial Services Healthcare Maritime and Retail.
- Build ingestion and transformation pipelines in Azure Fabric / Synapse / Databricks.
- Implement metadata-driven frameworks quality checks and monitoring dashboards.
- Enable self-service analytics and reporting pipelines.
- Collaborate with cross-functional teams to ensure secure governed and performant pipelines.
MUST HAVE EXPERIENCE
- 36 years of hands-on data engineering experience.
- Azure expertise: Azure Data Lake (ADLS Gen2/OneLake) Azure Data Factory/Fabric pipelines Synapse Analytics Databricks (Spark) Logic Apps.
- Strong Python and SQL skills.
- Experience implementing data quality rules and monitoring.
- Familiarity with RBAC Purview (governance & lineage).
GOOD TO HAVE
- AWS services: S3 Glue Lambda.
- GCP services: BigQuery Dataflow.
- Experience with real-time streaming (Event Hub Kafka Pub/Sub).
We will be prioritizing applicants who have a current right to work in Singapore and do not require sponsorship of a visa.
MORE ABOUT PALO IT:
Were eager to adapt to change learn from our experiences and move to meet our planets urgent needs. We are continuously taking action to:
- Become a climate net-zero company
- Attain 50% of revenue from projects with a positive impact
- Train 100% of our workforce on impact
- Achieve B Corp certification among all our offices across the globe
- Continuously measure & improve employee happiness
What We Offer
- Stimulating working environments
- Unique career path
- International mobility
- Internal R&D projects
- Knowledge sharing
- Personalized training
For more on our team culture and benefits check out our careers page.
PALO IT Singapore is an equal opportunity employer. Employment decisions will be based on merit qualifications and abilities. Palo IT SG does not discriminate in employment opportunities or practices on the basis of race colour religion sex sexuality national origin age disability marital status or any other characteristics protected by law.
Protecting your privacy and the security of yourdataare longstanding top priorities for Palo-IT.
Your personaldatawill be processed for the purposes of managing Palo-ITs recruitment related activities which include setting up and conducting interviews and tests for applicants evaluating and assessing the results and as is otherwise needed in the recruitment and hiring processes.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
PALO IT is a global innovation consultancy and Agile software development company dedicated to helping organisations embrace tech as a force for good.
