We are hiring for a business consulting and IT service company Business Intelligence data engineer work from home on 12 months and extendable contract.

Job Summary and Responsibilities

Design, develop, test, deploy and maintain ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks.
Implement scalable data processing and transformation logic in PySpark and SQL on Databricks (Delta Lake / lakehouse patterns). Ingest and integrate data from diverse batch and streaming sources into ADLS Gen2 and Delta Lake.
Build curated, documented datasets for analytics and ML (support dimensional models where appropriate).
Optimize pipeline performance and cost: cluster sizing, job scheduling, partitioning, caching and query tuning.
Implement and maintain CI/CD for data jobs and infrastructure (Terraform/ARM/Bicep, Azure DevOps or GitHub Actions).

Perform SAP BW (Business Warehouse) activities:

· Design, develop, and maintain enterprise data warehousing and reporting solutions.

· Build ETL processes, manage data models, and optimize system performance.

· Troubleshoot failed batch loads, fix data discrepancies and conduct root-cause analysis for production support.

Lead / perform Data Governance and Data Quality Engineering activities:

Data Governance:

· Define, maintain and version data standards, definitions and business glossary for in‑scope domains; deliver a single-source-of-truth catalog entry for each CDE.

· Document Critical Data Elements (CDEs) with classification (sensitivity/confidentiality), lineage, acceptable values, usage rules and retention.

· Facilitate the data ownership/stewardship model. Establish and publish roles, responsibilities, decision rights, and escalation paths.

Translate governance policies into technical and operational rules together with Data Engineers (naming conventions, modeling guidelines, access controls).

· Triage and coordinate remediation of data issues: maintain issue logs, lead RCA workshops, assign actions, and track SLAs to closure.

Define and monitor data governance and quality KPIs (completeness, accuracy, timeliness, uniqueness, policy adherence); agree baseline targets during onboarding and provide monthly dashboards.

· Support data access governance and privacy: participate in access reviews, assist Legal/Compliance on regulatory requests, and ensure controls meet policy (GDPR/CCPA as applicable).

· Create and run training, playbooks, onboarding kits for stewards and data consumers; recommend and help implement automation (catalog integrations, alerting).

· Act as liaison across business, analytics, engineering and compliance to balance risk mitigation and business enablement.

· Fluent English and Mandarin.

If this sounds like you then apply