Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data warehouse solutions to support business reporting and analytical requirements.
• Build and optimize data models, including dimensional models, star schemas, and snowflake schemas.
• Develop and manage data structures, tables, views, and relationships to ensure efficient data storage and retrieval.
• Implement data integration processes to consolidate information from multiple operational systems and external sources.
• Monitor data warehouse performance and optimize queries, indexing, and storage for improved efficiency.
• Ensure data quality, consistency, integrity, and security across warehouse environments.

• Design, build, and maintain reliable ETL/ELT pipelines for extracting, transforming, and loading data.
• Develop automated workflows to process structured and semi-structured data from different sources.
• Identify and troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.
• Implement validation checks and monitoring mechanisms to ensure data accuracy and pipeline reliability.
• Document data flows, transformation logic, and technical processes for maintainability.

• Develop scalable data processing solutions using appropriate programming languages and data technologies.
• Integrate data from databases, APIs, cloud platforms, and other business applications.
• Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
• Follow best practices for data governance, access control, security, and efficient data processing.
• Contribute to improving existing data architecture, automation, and engineering workflows.

• Work closely with data analysts and business teams to provide reliable, analysis-ready datasets.
• Support the development of dashboards, reports, and business intelligence solutions.
• Investigate data trends, anomalies, and discrepancies to identify potential data quality issues.
• Translate business requirements into appropriate data models and processing workflows.

Must-Have Skills

• Strong knowledge of Data Warehousing concepts and architecture.
• Experience with data modeling, ETL/ELT processes, and data integration.
• Proficiency in SQL and relational databases.
• Understanding of database performance optimization and data quality management.
• Strong analytical thinking, troubleshooting, and problem-solving abilities.

Good-to-Have Skills

• Experience in Data Engineering and building automated data pipelines.
• Knowledge of Data Analysis and business intelligence tools.
• Familiarity with Python or similar programming languages.
• Exposure to cloud data platforms and modern data warehouse technologies.
• Experience with workflow orchestration and data pipeline monitoring tools.

Qualifications and Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 3–5 years of relevant experience in data engineering, data warehousing, or database development.
• Strong communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.