Data Engineer

Key Responsibilities Data Architecture Design: Contribute to the design of scalable and secure data solutions, ensuring alignment with business and technical needs ETL/ELT Pipeline Development: Develop and optimize efficient pipelines to ingest, transform, and load data from diverse sources into structured formats for analytics Data Source Analysis: Analyze structured and unstructured data sources, recommending strategies for ingestion, processing, and classification Data Layer Development: Assist in building a robust data layer that supports both batch and real-time processing Data Ingestion & Cleansing: Implement strategies for validating and cleansing data to ensure quality and compliance with governance policies Query Optimization: Write and optimize SQL queries to improve performance and efficiency across large datasets Data Migration: Support migration projects from legacy systems to cloud platforms, ensuring accuracy and minimal downtime Performance Monitoring: Monitor data workflows, troubleshoot bottlenecks, and propose improvements Collaboration: Work closely with analysts, scientists, and business teams to translate requirements into data models Data Governance & Security: Apply governance standards and security best practices, ensuring compliance with regulations (e.g., GDPR) Continuous Learning: Stay updated on emerging tools and practices, contributing to team innovation and improvement Qualifications 4+ years of experience in data engineering or related roles Strong knowledge of SQL, relational databases, and query optimization Hands-on experience with ETL/ELT tools and cloud platforms (AWS, Azure, or GCP) Familiarity with data governance, security, and compliance frameworks Solid understanding of batch and real-time data processing Collaborative mindset with ability to work across technical and business teams Show more