Data Engineer - Microsoft Fabric: Lakehouse Pipelines (Remote)

Emapta

Metro Manila

Remote

PHP 900,000 - 1,500,000

Full time

7 days ago

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Benefits offered by this job

Day 1 HMO coverage with free dependent

Competitive Salary Package

Day Shift Schedule

Permanent WFH arrangement

Fixed weekends off

Salary Advance Program

Upskilling via Emapta Academy

Gym access and trainer

Lifestyle perks

Employee referral incentives

Government and Emapta benefits

Annual leave: 20 days

Mentorship and exposure to globalLeads

Career growth opportunities

Job summary

Emapta is seeking a Data Engineer (Microsoft Fabric) to design and maintain scalable lakehouse architectures and secure analytics solutions for a global client. You will develop production data pipelines, utilize OneLake and Fabric Data Factory, and deliver Power BI insights while collaborating with international teams from a work-from-home setup.

Join a team focused on advanced data engineering, governance, security, and continuous learning, with clear growth pathways and a permanent WFH

Qualifications

3 to 5 years of relevant experience in data engineering with Microsoft Fabric and enterprise data solutions.
Proven experience in the development and support of production data pipelines, lake houses, and data warehouses within Microsoft Fabric.
Strong proficiency in SQL and Python/PySpark, with practical experience in data transformation, query optimization, debugging, and source control.
Hands-on experience with Fabric Data Factory, notebooks, OneLake, and lakehouse or warehouse workloads, complemented by Power BI and Fabric Apps delivery experience.
Experience in database, API, and file integration; incremental data loads; dimensional modeling; and the implementation of data quality, identity, security, and privacy controls.
Experience in production system support, including monitoring, troubleshooting, incident response, and continuous improvement.
Experience in outsourced or distributed team environments, with the ability to meet client priorities, project deliverables, acceptance criteria, and support requirements

Responsibilities

Translate approved business requirements into practical data engineering tasks, effort estimates, and technical designs, with clearly defined dependencies and acceptance criteria.
Escalate proposed scope changes for review and approval.
Build and maintain Microsoft Fabric pipelines, notebooks, lakehouses, and warehouses for production data workloads.
Develop and optimize SQL and Python/PySpark transformations and reusable data ingestion components for enterprise systems, databases, files, and APIs.
Transform Silver-layer data into reusable, analytics-ready Gold-layer models within Microsoft Fabric.
Apply approved business definitions, incremental data processing techniques, and appropriate data aggregations.
Apply Kimball dimensional design principles to define business processes and fact-table granularity.
Develop star schemas with conformed dimensions, surrogate keys, and slowly changing dimensions where appropriate.
Support Power BI semantic models, measures, and standard reports that use Gold-layer data.
Validate data refresh processes, filter behavior, and aggregation accuracy across Power BI solutions.
Collaborate with report developers and application specialists to develop and maintain Fabric Apps connected to approved data products.
Maintain data engineering as the primary technical focus throughout application integration and delivery.
Implement data quality checks, reconciliation controls, and procedures to manage incomplete, duplicate, or invalid records.
Maintain data model definitions, relationships, source-to-target mappings, data lineage, and operational runbooks.
Transfer technical knowledge to support governance reviews, service continuity, planned absences, and provider transitions.
Apply approved identity management, least-privilege access, secrets management, and remote-access controls.
Use authorized workspaces, connectors, data sources, and storage locations; prevent unauthorized local copies or data transfers and elevate exceptions.
Monitor data reliability and access controls, and support the resolution of data quality, security, privacy, and compliance issues.
Execute functional, integration, performance, and security tests to verify solution quality and reliability.
Document test evidence, resolve defects, and support client-led user acceptance testing (UAT) and release approvals.
Use client-controlled repositories, code reviews, and repeatable deployment processes.
Maintain source code and configuration files to support environment promotion, technical reviews, and acceptance.
Implement pipeline monitoring, operational logs, failure alerts, recovery procedures, and capacity-aware performance optimization.
Investigate failed data loads, data discrepancies, and performance issues within agreed support hours and service targets.
Escalate incidents promptly through approved client and service provider channels and implement sustainable corrective solutions.
Collaborate remotely with Australian product owners, delivery leads, engineers, analysts, architects, security teams, and business specialists.
Maintain agreed overlap with Australian business hours to support effective project coordination.
Maintain project delivery records and provide regular progress, effort, and forecast updates.
Identify and elevate blockers, dependencies, and project risks at an early stage.
Explain technical options clearly and demonstrate completed solutions to relevant stakeholders.
Contribute reusable components, technical standards, and lessons learned to the enterprise data engineering practice.
About the Client - Our client is a leading Australian food services and facilities management provider backed by a global network.