Data Engineer

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).