Data Engineer

Role Overview The Data Engineer is responsible for designing, developing, and maintaining scalable data architectures and pipelines that enable the efficient collection, transformation, and utilization of data across the organization. This role ensures that high-quality, reliable, and well-structured data is available for analytics, reporting, and machine learning applications. Working closely with data scientists, analysts, and software engineers, the Data Engineer plays a key role in optimizing data flow, automating processes, and enhancing data-driven decision-making. This position is ideal for technically skilled professionals who enjoy working with complex datasets and developing innovative data solutions in a fast-paced, technology-driven environment.Key ResponsibilitiesDesign, build, and maintain data pipelines and ETL (Extract, Transform, Load) workflows to support data analytics and business intelligence initiatives.Develop and optimize data architectures that ensure scalability, performance, and reliability.Integrate data from various internal and external systems while ensuring data accuracy and consistency.Collaborate with data scientists and analysts to prepare clean and structured datasets for analysis and modeling.Implement data quality checks, validation procedures, and governance policies.Manage databases, data warehouses, and data lakes across on-premise and cloud environments.Automate data processes using programming and scripting languages.Monitor, troubleshoot, and optimize data workflows to ensure continuous and efficient operations.Ensure data security, privacy, and compliance with internal and external regulations.Document data models, architecture designs, and processes for cross-functional understanding.Qualifications and RequirementsBachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.2–5 years of experience in data engineering, data warehousing, or a related technical discipline.Strong proficiency in SQL and programming languages such as Python, Java, or Scala.Experience with ETL tools and data integration platforms (e.g., Apache Airflow, Talend, or Informatica).Hands-on experience with cloud-based data platforms (AWS, Azure, or Google Cloud) and tools such as Redshift, BigQuery, or Snowflake.Knowledge of big data frameworks like Apache Spark, Hadoop, or Kafka.Familiarity with data modeling, schema design, and database optimization techniques.Understanding of APIs, microservices, and real-time data processing.Strong analytical, problem-solving, and troubleshooting abilities.Effective communication and teamwork skills to collaborate with technical and non-technical stakeholders.Experience with DevOps tools and version control systems (Git, CI/CD pipelines) is a plus.Summary The Data Engineer plays a crucial role in building the infrastructure that supports data-driven decision-making across the organization. By developing scalable data systems and ensuring the integrity and accessibility of data, this position enables teams to leverage insights for innovation and growth. Ideal for professionals passionate about data architecture and technology, the role offers opportunities to work on cutting-edge projects, implement advanced data solutions, and contribute to the evolution of modern data ecosystems.