Overview: This role focuses on backend development and integrations for building and maintaining enterprise data warehouses and data lakes. The ideal candidate will possess a deep understanding of data architecture, ETL pipelines, and integration technologies, ensuring seamless data flow and accessibility across the organization. Key Responsibilities: · Design, develop, and maintain scalable backend systems to support data warehousing and data lake initiatives. · Build and optimize ETL/ELT processes to extract, transform, and load data from various sources into centralized data repositories. · Develop and implement integration solutions for seamless data exchange between systems, applications, and platforms. · Collaborate with data architects, analysts, and other stakeholders to define and implement data models, schemas, and storage solutions. · Ensure data quality, consistency, and security by implementing best practices and monitoring frameworks. · Monitor and troubleshoot data pipelines and systems to ensure high availability and performance. · Stay up-to-date with emerging technologies and trends in data engineering and integration to recommend improvements and innovations. · Document technical designs, processes, and standards for the team and stakeholders. Qualifications: · Bachelor’s degree in Computer Science, Engineering, or a related field; equivalent experience considered. · Proven experience as a Data Engineer or in a similar backend development role. · Strong proficiency in programming languages such as Python, Java, or Scala. · Hands-on experience with ETL/ELT tools and frameworks (e.g., Apache Airflow, Talend, Informatica, etc.). · Extensive knowledge of relational and non-relational databases (e.g., SQL, NoSQL, PostgreSQL, MongoDB). · Expertise in building and managing enterprise data warehouses (e.g., Snowflake, Amazon Redshift, Google BigQuery) and data lakes (e.g., AWS S3, Azure Data Lake). · Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their data services. · Experience with API integrations and data exchange protocols (e.g., REST, SOAP, JSON, XML). · Solid understanding of data governance, security, and compliance standards. · Strong analytical and problem-solving skills with attention to detail. · Excellent communication and collaboration abilities. Preferred Qualifications: · Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.) · Experience with big data technologies (e.g., Apache Hadoop, Spark, Kafka). · Knowledge of data visualization tools (e.g., Tableau, Power BI) for supporting downstream analytics. · Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes, Jenkins).