Data Engineer

As a Data Engineer at Intellectsoft, you'll be responsible for designing, building, and maintaining reliable data pipelines that ingest data from diverse sources, including internal systems and APIs. You'll work with various types of data to ensure quality and consistency, develop ETL processes for both real-time and batch analytics, and collaborate closely with Data Architects to create optimal data models for analytics workloads. Additionally, you'll contribute to data governance and be part of performance optimization efforts to keep our platform at peak efficiency.

To become a Data Engineer at Intellectsoft, you should have a solid five years of experience in data engineering or backend data development. Proficiency in SQL and familiarity with a programming language like Python or Scala is essential. Experience with cloud or hybrid data architectures, as well as real-time data streaming frameworks, would also be advantageous. A good understanding of data security and compliance best practices, along with prior work in Agile environments, completes the ideal candidate profile.

In your daily role as a Data Engineer at Intellectsoft, you'll leverage your expertise in designing scalable data pipelines, transforming data, and ensuring data integrity. You'll regularly use tools for data ingestion and data processing, often utilizing your SQL skills for querying and managing data. Additionally, you may work with distributed data processing tools like Spark or Flink, enhancing your familiarity with data lakes, warehouses, and best practices for data governance and privacy.

As a Data Engineer at Intellectsoft, you'll experience a collaborative and innovative work environment. We're dedicated to Agile principles and encourage teamwork with Data Architects, ML Engineers, and Business Analysts. Our culture promotes flexibility, allowing you to take advantage of 35 absence days for work-life balance, engage in professional development through Udemy courses, and participate in team-building activities that foster camaraderie and growth.

Yes! Data Engineers at Intellectsoft enjoy a range of unique benefits, including 35 absence days for optimal work-life balance and access to learning through Udemy courses of your choice. Additionally, we offer English courses with native speakers, and regular soft-skills training to enhance your overall professional development. You can also look forward to excellence center meetups and both online and offline team-building events, ensuring you not only grow professionally but also enjoy a fulfilling work culture.

When answering this question, outline the project's objectives, the tools and technologies you utilized, and any challenges you faced during the implementation. Emphasize how your design decisions affected the efficiency and reliability of the pipeline, and highlight any quantifiable results or improvements that emerged from your work.

Discuss the practices you adopt to maintain data quality, such as data validation techniques, deduplication processes, and consistent data transformation logic. Provide examples of specific tools or methods you've used to monitor and evaluate data quality over time, and any frameworks you’ve implemented for tracking and addressing data issues.

To effectively respond, outline the ETL/ELT processes you've implemented in past roles, describing the various stages from data extraction to transformation and loading. Talk about the tools you've used and how you tailored the processes to meet business-specific needs, showcasing your ability to handle both batch and real-time data.

Highlight your experience with cloud platforms such as AWS, Google Cloud, or Azure. Discuss specific services you’ve used for data storage, processing, or analytics. Provide examples of projects where cloud architectures played a crucial role, and emphasize your understanding of deployment priorities like scalability and cost management.

Discuss your knowledge of best practices in data security, including encryption techniques, user access controls, and compliance with regulations like GDPR. Provide specific examples of how you've implemented these principles in your work to protect sensitive data and ensure regulatory compliance.

Describe how you have utilized Agile methodologies in past projects, detailing your role in ensuring team success. Provide examples of how you collaborated with other team members and adapted to feedback to improve deliverables, highlighting your commitment to iterative development and continuous improvement.

Share specific challenges you faced, such as data processing speed or quality issues with large datasets. Discuss the strategies you employed to overcome these challenges, such as optimizing queries or implementing distributed processing tools, showcasing your problem-solving skills and adaptability.

Highlight your experience working alongside business analysts, marketing teams, or other non-technical stakeholders. Discuss how you translated technical requirements into actionable insights and facilitated communication to ensure cohesive project outcomes, illustrating your collaborative spirit and ability to bridge technical gaps.

List the business intelligence (BI) tools and visualization software you've used, such as Tableau, Power BI, or Looker. Discuss how you've applied these tools to create meaningful dashboards or reports that delivered insights to stakeholders, emphasizing your ability to convey complex data simply.

Explain your knowledge or experience with data streaming technologies like Apache Kafka or AWS Kinesis. Discuss how you've implemented these technologies in projects to handle real-time data, highlighting your understanding of their capabilities and the value they bring to data-driven decision-making.