Senior Data Engineer - Snowflake

As a Senior Data Engineer at Accellor, you will take ownership of technical solutions, design architectures, and oversee the implementation of multiple complex projects. Your duties will also include gathering end-user requirements, writing technical documentation, and reviewing technological solutions to ensure they meet client needs. You'll play a critical role in collaborating with client teams to identify pain points and propose ideal solutions, making it essential to have strong problem-solving and communication skills.

To be a successful candidate for the Senior Data Engineer role at Accellor, you should possess at least 7 years of experience in data engineering or architecture, particularly with Snowflake. Strong expertise in SQL and advanced query optimization techniques is required, along with hands-on experience with cloud platforms like AWS, Azure, or GCP. Familiarity with ETL/ELT tools and programming languages such as Python, Java, or Scala will also enhance your application.

In the Senior Data Engineer role at Accellor, you'll be working primarily with Snowflake for data warehousing solutions. Additionally, you'll utilize cloud platforms such as AWS, Azure, or GCP, along with ETL/ELT tools like ADF and Fabric. Data visualization tools like Tableau, Power BI, or Looker will be part of your toolkit, complemented by your programming skills in languages such as Python or Java for data processing and automation.

Accellor is committed to the continuous professional growth of its team members. As a Senior Data Engineer, you will have access to a dedicated Learning & Development team that organizes various training programs, including technical skills development, soft skills training, and professional certifications. This commitment to learning fosters an environment where employees can expand their skills and stay updated with the latest industry trends and technologies.

Accellor prides itself on fostering a collaborative and laid-back work environment. As a Senior Data Engineer, you'll be part of a diverse team, where curiosity and innovation are encouraged. The company promotes work-life balance through flexible schedules, remote work opportunities, and generous leave policies, allowing you to thrive both professionally and personally.

In your response, highlight specific projects where you utilized Snowflake, detailing the challenges you faced and how you overcame them. Discuss any data transformation, warehouse design, or performance optimization techniques you employed, showcasing your technical expertise and problem-solving skills.

Explain your methodology for engaging with stakeholders to understand their needs. Emphasize active listening, asking clarifying questions, and documenting requirements thoroughly to ensure that the final solution aligns with user expectations and business goals.

Share your knowledge of indexing, using EXPLAIN plans, or other optimization techniques you’ve applied in Snowflake. Provide examples of situations where you improved query performance, emphasizing results achieved through your optimization efforts.

Reflect on a specific instance where you learned a new tool or technology, describing how you approached the learning process, the impact it had on your work, and how you integrated it into your daily tasks or projects.

Talk about the importance of setting clear communication expectations and being proactive in updates. Mention techniques like regular check-ins, using visual aids for clarification, and adopting a client-first mindset to foster collaborative relationships.

Discuss the specific ETL/ELT tools you’ve worked with, like ADF or Fabric, and detail your experience in designing and implementing data pipelines. Highlight how you ensured data quality and efficiency in your engineering processes.

Share a specific challenge you encountered, detailing the steps you took to analyze the situation, the solution you crafted, and the positive outcome that resulted. Focus on your problem-solving approach and any lessons learned.

Provide an overview of the integration process, mentioning the cloud platforms you've used (like AWS, Azure, or GCP) and the role each played in supporting data storage and processing. Discuss any specific tools or configurations you’ve worked with to facilitate this integration.

Illustrate your time management and organizational skills by describing your approach to prioritizing tasks, such as using tools for tracking progress, staying focused on deadlines, and ensuring that you allocate time for strategic project reviews.

Discuss the data visualization tools you’ve worked with, such as Tableau, Power BI, or Looker, and explain how they facilitate data-driven decision-making. Highlight specific projects where data visualization significantly impacted stakeholder understanding and project success.