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Job Description:
We are seeking a skilled and experienced Data Engineer to join our dynamic team. As a Data Engineer, you will be responsible for designing, developing, and maintaining our company's data architecture and infrastructure. You will work closely with cross-functional teams to understand data requirements, build data pipelines, and ensure data quality and integrity. The ideal candidate should have a strong background in data engineering, database management, and data warehousing technologies.

Roles and Responsibilities:

Data Pipeline Development: Design, develop, and maintain scalable and efficient data pipelines to ingest, process, and transform large volumes of structured and unstructured data from diverse sources.

Data Modeling and Architecture: Design and implement data models, schemas, and database architectures to support business requirements and analytical needs. Optimize data storage and retrieval processes for performance and scalability.

ETL (Extract, Transform, Load): Develop and maintain ETL processes to extract data from various sources, transform it into usable formats, and load it into data warehouses or analytical systems. Ensure data accuracy, completeness, and consistency throughout the ETL lifecycle.

Data Integration and Transformation: Integrate disparate data sources and formats using appropriate tools and techniques. Perform data cleansing, normalization, and enrichment to enhance data quality and usability.

Data Governance and Security: Implement data governance policies, standards, and procedures to ensure data privacy, compliance, and security. Monitor data access, usage, and permissions to prevent unauthorized access or data breaches.

Performance Optimization: Identify and resolve performance bottlenecks in data pipelines, queries, and processing tasks. Tune database configurations, indexes, and queries for optimal performance and resource utilization.

Monitoring and Troubleshooting: Monitor data pipelines, jobs, and workflows to ensure smooth operation and timely data delivery. Troubleshoot and resolve issues related to data ingestion, processing, or integration failures.

Collaboration and Documentation: Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs. Document data pipelines, processes, and workflows for knowledge sharing and future reference.

Continuous Learning and Innovation: Stay updated with the latest trends, technologies, and best practices in data engineering and analytics. Continuously evaluate and adopt new tools, frameworks, and methodologies to improve efficiency and effectiveness.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Proven experience in data engineering, database development, or related roles.
Proficiency in programming languages such as Python, Java, or Scala.
Strong SQL skills with experience in relational and non-relational databases.
Hands-on experience with data warehousing platforms (e.g., Amazon Redshift, Google BigQuery, Snowflake) and cloud services (e.g., AWS, Azure, GCP).
Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and distributed computing frameworks.
Excellent problem-solving skills with the ability to analyze complex data issues and propose effective solutions.
Strong communication and interpersonal skills with the ability to collaborate effectively in a team environment.