We are seeking an experienced Data Engineer with a background in data integration, ETL processes, and data warehousing. The ideal candidate will have 5-7 years of experience in data engineering, with advanced knowledge of data architecture, pipeline creation, and big data technologies. This role demands a proactive individual skilled in designing, building, and maintaining data systems, collaborating with cross-functional teams, and ensuring the highest standards of data quality and performance.
Job ResponsibilitiesDesign, develop, and maintain scalable data pipelines for data ingestion, processing, and storage.Build and optimize data architectures and data models for efficient data storage and retrieval.Develop complex ETL processes to transform and load data from various sources into data warehouses and data lakes.Ensure data integrity, quality, and security across all data systems.Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.Monitor, troubleshoot, and optimize data pipelines and workflows to ensure high availability and performance.Document data processes, architectures, and data flow diagrams.RequirementsCandidate Required SkillsBachelor's degree in Computer Science, Engineering, or a related field.5-7 years of experience in data engineering and data architecture.Proficiency in SQL and at least one programming language (e.g., Python, Java, Scala).Advanced experience with cloud data platforms (e.g., AWS, Azure, GCP) and their data services.Strong knowledge of ETL tools and frameworks (e.g., Apache NiFi, Talend, Informatica).Expertise in data modeling, data structures, and database design.Strong analytical and problem-solving skills, with the ability to handle complex data challenges.Excellent communication and collaboration skills, with the ability to work independently and as part of a team.Experience with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka).Knowledge of data governance and best practices in data management.Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).Experience with data visualization tools (e.g., Tableau, Power BI).
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