Data & Analytics Engineer

About the Role

We seek a proficient Data & Analytics Engineer to architect, develop, and sustain scalable data pipelines plus reporting solutions. The successful candidate will demonstrate practical expertise in cloud-based data warehousing, building ETL/ELT pipelines, and utilizing business intelligence software to empower the company with dependable, structured data to guide data-driven decisions.

Key Responsibilities

• Create, enhance, and sustain strong ETL and ELT pipelines via Azure Data Factory (ADF) for gathering, converting, and loading data across diverse sources.
• Construct and fine-tune data models and pipelines within Azure Synapse Analytics to promote data warehousing and analytical effectiveness.
• Handle, query, and refine large-scale datasets in Google BigQuery tailored for analysis workloads.
• Develop dynamic dashboards, reports, and visual displays using Power BI catering to business stakeholders’ requirements.
• Craft efficient, optimized SQL queries for data extraction, transformation, and detailed analysis on various platforms.
• Preserve high standards of data quality, consistency, and integrity throughout pipelines and reporting layers.
• Collaborate with business analysts, data scientists, and relevant stakeholders to gather and understand reporting and data-related needs.
• Track and resolve performance issues in data pipelines, ensuring data is delivered punctually and accurately.
• Adopt and enforce best practices related to data governance, security protocols, and thorough documentation.
• Assist in ad-hoc data demands and analytical tasks as requested by business units.

Qualifications & Skills

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a closely related discipline.
• Significant experience in data engineering, analytics engineering, or comparable roles.
• Expertise in Google BigQuery encompassing optimized query writing, dataset management, and performance tuning.
• Proficiency in Power BI for dashboard creation, DAX, data modeling, and report publication.
• Competence with Azure Synapse Analytics in data warehousing and integration of pipelines.
• Hands-on experience with Azure Data Factory for orchestrating pipelines and managing data ingestion and transformation workflows.
• Advanced SQL skills including crafting queries, stored procedures, and optimizing performance.
• Solid grasp of data warehousing principles, dimensional modeling, and ETL/ELT best practices.
• Experience processing structured and semi-structured data such as CSV, JSON, and Parquet formats.
• Strong analytical thinking and problem-solving ability with meticulous attention to detail.
• Effective communication skills to collaborate with cross-functional teams and translate business requirements into technical tasks.

Preferred Qualifications

• Experience using Python or PySpark for data processing tasks.
• Awareness of additional cloud platforms beyond Azure and BigQuery, including AWS and GCP.
• Knowledge of CI/CD methodologies for deploying data pipelines.
• Understanding of data governance and security frameworks.
• Previous work experience in sectors such as banking, retail, or healthcare is advantageous.