Data Engineer Job

Design, build, and maintain efficient and scalable data pipelines to extract, transform, and load (ETL) structured and unstructured data. Collaborate with data scientists and business analysts to understand data requirements and ensure data availability and quality. Implement data validation and quality checks to ensure accurate and reliable data for downstream processes.
Develop and implement data models to support data analytics and machine learning algorithms.
Integrate data from various sources, including databases, APIs, and external systems, ensuring data quality and consistency.
Design and manage data warehouse systems, optimizing data storage and retrieval for efficient analytics.
Develop and implement data validation and quality checks to ensure accuracy, completeness, and consistency of data.
Identify and resolve performance bottlenecks in data processing and analytics workflows, optimizing query performance and data processing speed.
Analyze large, complex datasets to extract valuable insights and provide recommendations for improving business operations.
Write clean, efficient, and maintainable code following best practices and coding standards. Identify and optimize software programs, scripts, or algorithms to improve data processing and analytics performance.
Monitor and assess database performance metrics, identify areas for improvement, and implement enhancements.
Managing and Implementation of High Availability and Disaster Recovery Solutions using AlwaysON Availability groups.
Manage Database Backups and Recovery processes to meet RTO and RPO.
Implementing and maintaining database security measures to meet industry compliance standards.
Collaborate with cross-functional teams, including data scientists, software engineers, and IT personnel, to resolve technical issues.
Design and implement testing routines or procedures to ensure data accuracy, system functionality, and performance.
Cleanse, transform, and format raw data into suitable formats for analysis, ensuring data integrity and compatibility with analytics tools.
Collaborate with data scientists, software engineers, and other stakeholders to understand requirements and deliver AI solutions. Participate in code reviews and offer constructive feedback to improve code quality and adherence to standards.
Document data engineering processes, workflows, and best practices to facilitate knowledge sharing and ensure reproducibility of results. Documenting data processes, schemas, and metadata to ensure that data is understandable and usable by other team members.
Stay up-to-date with industry trends, emerging technologies, and best practices in data engineering and analytics. Conduct research and experimentation to explore new data engineering technologies or approaches that can enhance solution quality.
Provide technical support and troubleshooting assistance to resolve data engineering issues and ensure seamless data flow.

Please mail resumes to:

Dyads Consulting, LLC
Human Resources
2002 Academy Lane
Suite 230A-20
Farmers Branch TX 75234