Data Engineer

Adlab Solutions is seeking a motivated and detail-oriented Data Engineer to join our dynamic team. In this role, you will leverage your technical expertise to design, build, and maintain robust data pipelines and data warehouse architectures. You will work closely with data scientists, analysts, and other stakeholders to ensure the availability, reliability, and efficiency of data systems that support various business functions and decision-making processes. With an understanding of key data management concepts and best practices, you will play a crucial role in transforming raw data into actionable insights that drive strategic initiatives. The ideal candidate will possess strong skills in Python, SQL, and data warehousing, as well as a willingness to continuously learn and adapt to new technologies in the evolving field of data engineering. This position is perfect for individuals looking to grow their careers in data engineering within a collaborative environment, focusing on effective communication and fast learning to contribute to the overall success of Adlab Solutions. As a Data Engineer, your responsibilities will include the development and optimization of ETL processes, data modeling, and maintaining data integrity across various platforms. You will be expected to implement best practices for data collection and storage, ensuring the security and accuracy of data at all times. The role does not include managing a team, allowing you to concentrate on your technical skills and project contributions while collaborating closely with other team members to achieve effective outcomes.

Responsibilities

Design, develop, and maintain scalable data pipelines to efficiently handle data from various sources.
Implement ETL processes to extract, transform, and load data into data warehouses.
Utilize data modeling techniques to organize and structure data effectively for analysis and reporting.
Work with SQL to query and manipulate large datasets ensuring data accuracy and reliability.
Integrate and configure data storage solutions on AWS to optimize performance and cost-effectiveness.
Collaborate with data scientists and analysts to understand data needs and provide the required datasets.
Monitor and enhance existing data systems for performance tuning and reliability.
Conduct routine data quality assessments and troubleshoot issues as they arise.
Document data processes and transformations clearly for future reference and compliance.
Stay updated on emerging technologies and best practices in data engineering and apply them effectively.