Job Description:Responsibilities:Data Architecture and Design: Design and implement scalable and efficient data architectures, including data warehouses, data lakes, and data marts. Define data models, schemas, and standards to ensure consistency and reliability across the organization.Data Pipeline Development: Develop and maintain robust data pipelines and ETL processes to ingest, transform, and load large volumes of data from various sources. Implement data integration solutions to enable seamless data flow between systems and applications.Database Management and Optimization: Manage and optimize database systems, including relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra). Perform performance tuning, indexing, and query optimization to ensure optimal database performance.Data Quality Assurance: Implement data quality assurance processes to monitor and maintain data quality and integrity. Develop data validation checks, error handling mechanisms, and data cleansing procedures to ensure accuracy and reliability of data.Big Data Technologies: Utilize big data technologies and frameworks, such as Apache Spark, Hadoop, or Kafka, to process and analyze large-scale data sets. Design and implement distributed data processing solutions for real-time and batch processing applications.Cloud Data Platforms: Work with cloud data platforms, such as AWS, Azure, or Google Cloud Platform, to deploy and manage data infrastructure in the cloud. Leverage cloud-native services for data storage, processing, and analytics.Data Security and Compliance: Implement data security measures and compliance controls to protect sensitive data and ensure regulatory compliance. Implement access controls, encryption, and auditing mechanisms to safeguard data privacy and security.Monitoring and Troubleshooting: Monitor data pipelines, systems, and infrastructure components for performance, reliability, and availability. Identify and troubleshoot issues, bottlenecks, and performance degradation to ensure smooth operation of data systems.Documentation and Documentation: Document data architectures, designs, and processes to ensure comprehensive and up-to-date documentation. Create technical documentation, data flow diagrams, and system diagrams to facilitate knowledge sharing and collaboration.Qualifications:Education: Bachelor's degree in computer science, engineering, mathematics, or a related field. Advanced degree or relevant certifications in data engineering, database management, or cloud computing is a plus.Experience: 4-7 years of experience in data engineering or a related field, with a focus on building and maintaining data infrastructure. Proven track record of successfully delivering data projects and initiatives.Technical Skills: Strong proficiency in data engineering technologies and tools, including database systems, ETL frameworks, big data platforms, and cloud services. Expertise in programming languages such as Python, Java, Scala, or SQL.Analytical Skills: Strong analytical and problem-solving skills, with the ability to analyze complex data sets and derive meaningful insights. Experience with data analysis, data modeling, and statistical analysis techniques.Communication Skills: Excellent written and verbal communication skills, with the ability to communicate technical concepts to both technical and non-technical audiences. Ability to collaborate effectively with cross-functional teams and stakeholders.Leadership and Collaboration: Demonstrated leadership skills, with the ability to lead data engineering projects and initiatives. Experience working collaboratively in a team environment and providing guidance to junior team members.