Data Engineer

As a Data Engineer at Derex Technologies Inc, your main responsibilities will include designing, developing, and implementing data warehousing applications using ETL tools, specifically IBM Infosphere DataStage. You'll be tasked with creating and maintaining data pipelines that efficiently handle the extraction, transformation, and loading (ETL) of both structured and unstructured data. Collaboration with other data professionals to ensure optimal data flow and leveraging AWS tools to provide scalable solutions will also be key components of your role.

To qualify for the Data Engineer position at Derex Technologies Inc, you should have a minimum of 5-7 years experience in data engineering, particularly with ETL tools like IBM DataStage. You should also have strong skills in SQL and PL/SQL, with proficiency in Unix shell scripting. Knowledge of AWS cloud infrastructure services such as EC2, S3, and VPC is essential, as well as exposure to modern data architectures and analytics tools like Python and R.

At Derex Technologies Inc, we prioritize your professional development as a Data Engineer. We offer various training programs and resources to help you stay updated with the latest technologies in data engineering and cloud computing. Additionally, you'll have opportunities to work on exciting projects across diverse industries, allowing you to broaden your skillset and gain valuable experience in the field.

The work environment at Derex Technologies Inc for a Data Engineer is collaborative and innovative. You will be part of a supportive team that values creativity and encourages knowledge-sharing. Our culture emphasizes transparency and open communication, and we provide a flexible work environment that supports work-life balance while focusing on delivering top-quality technology solutions to our clients.

As a Data Engineer at Derex Technologies Inc, you will primarily work with IBM Infosphere DataStage for ETL processes, along with various AWS tools like EC2, S3, EBS, and VPC. Additionally, you will be familiar with SQL and PL/SQL for database querying and transformation, as well as Unix shell scripting for process automation. Knowledge of advanced analytics tools such as Python and R will also be beneficial in this role.

In answering this question, highlight specific projects where you've designed or implemented ETL workflows using IBM DataStage. Discuss your approach to handling data quality, transformations, and how you've optimized performance for high-volume data. Be sure to mention any encountered challenges and how you successfully addressed them.

When discussing performance tuning, explain your methodology, including tools you utilize for monitoring, as well as adjustment techniques like indexing and query optimization. Provide examples of how you've improved data processing times and mention key metrics you've monitored to measure success.

Speak to your specific experience with AWS services relevant to data engineering, such as EC2 for computing, S3 for storage, and VPC for network configuration. Provide examples of projects where you leveraged these services to create scalable and efficient data solutions and how you ensured data security throughout the process.

In your response, share a scenario where you effectively managed both types of data. Discuss the tools you used for extraction, transformation, and loading of each data type, highlighting any distinct challenges and how you successfully resolved them to deliver clean, usable data.

Discuss your proficiency with scripting languages such as Unix shell, Python, or Ruby. Provide examples of how you've automated processes or scheduled jobs using scripts, including any challenges you overcame and how these scripts improved your team's productivity and data management.

Here, it's essential to give a detailed account of the problem you faced, the steps you took to identify the root cause, and how you resolved the issue. Discuss any tools you used to monitor the data flow and how you communicated with your team during the troubleshooting process.

Talk about data validation techniques you implement during the ETL process, such as data profiling, cleansing, and monitoring for anomalies. Provide specific examples where you've enhanced data quality in projects and the impact it had on decision-making.

Explain your experience with tools like Python and R. Elaborate on how you have used these tools for data exploration, statistical analysis, or implementing machine learning algorithms. Provide specific examples from your work that illustrate your proficiency and the outcomes.

Share your approach to staying updated in the field, which might include attending workshops, webinars, following industry blogs, or participating in professional groups. Mention any recent trends you have adopted or are aware of, and how they may influence your future work as a Data Engineer.

Express your enthusiasm for the position by aligning your career goals with the values and opportunities at Derex Technologies Inc. Highlight your interest in working in diverse industry contexts, commitment to quality solutions, and enthusiasm for contributing to a team that prioritizes innovation and collaboration.