Data Engineer
Summary
A data engineer at Nezda Technologies in Muntinlupa designs data models, builds ETL pipelines, and develops Power BI dashboards across AWS and Azure cloud environments, while ensuring data governance and mentoring junior staff. Core stack: Python, SQL, PySpark, Azure Data Factory, Synapse, and Power BI.
Key Responsibilities
Data architecture & engineering – Design and implement logical/physical data models, build data marts, and manage ETL pipelines across cloud and hybrid environments.
Business intelligence – Develop dashboards, reports, and KPIs using Power BI, Synapse, and other visualization tools to deliver meaningful business insights.
Innovation – Apply open‑source and cloud technologies to mine complex datasets, automate workflows, and build self‑service frameworks.
Data management & governance – Ensure data quality, lineage, and metadata standards; manage security and access governance.
Collaboration – Partner with business and tech teams to align solutions with strategic goals, while mentoring junior engineers and analysts.
Required Qualifications
Education: Bachelor’s degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, or related).
Experience:
5+ years in cloud data engineering and analytics.
Multiple full life‑cycle data warehouse implementations.
2+ years in data analytics, with scripting and BI visualization experience.
Technical Skills:
Python, SQL, PySpark.
AWS Services, Azure Data Factory, Synapse,
Power BI, semantic modeling, dashboard development.
Data modeling tools (ER/Studio, ER/Win).
Cloud architecture competency and API development.
Familiarity with AWS services (Glue, S3, Athena, Redshift)
Exposure to Microsoft Fabric, Cosmos DB, Azure Databricks.
Knowledge of Agile, Lean, or Six Sigma methodologies.
Experience with data governance and quality tools (e.g., Informatica DQ).