Senior Data Engineer

As a Senior Data Engineer at Gridware, your responsibilities will include designing, developing, and maintaining scalable data pipelines and architectures. You will implement data ingestion, transformation, and storage solutions while ensuring data quality and integrity across various sources. Collaborating closely with software engineers and data scientists, you’ll optimize workflows for performance and troubleshoot any issues in data pipelines. Additionally, documenting data processes is crucial to support team collaboration and knowledge sharing.

Gridware is looking for candidates with over 5 years of experience in data engineering or a closely related field. Proficiency in SQL and experience with relational and time series databases is essential. You should have hands-on experience with big data technologies such as Hadoop, Spark, and Kafka, along with proficiency in Python. Familiarity with data modeling, ETL processes, data governance, and security best practices will also set you apart as a strong candidate.

In the Senior Data Engineer role at Gridware, you will work with a variety of tools and technologies including SQL for database management, Databricks for data engineering tasks, and Grafana for data visualization. Additionally, experience with big data technologies like Hadoop and Spark, as well as real-time processing frameworks, will be crucial. Familiarity with containerization tools such as Docker and Kubernetes is a great bonus, enhancing your ability to manage deployments effectively.

The Senior Data Engineer at Gridware plays a pivotal role in supporting the company’s mission to enhance and protect the electrical grid. By designing efficient data pipelines and ensuring the integrity of sensor data, you’ll help enable real-time analysis that can preemptively identify grid faults. This role directly contributes to bolstering safety and sustainability in our power infrastructure, making a tangible impact on the community and the environment.

Gridware offers an attractive benefits package for the Senior Data Engineer position, including comprehensive health, dental, and vision plans. Unique perks such as paid parental leave, alternating days off, and a special 'Off the Grid' two-week paid break program demonstrate the company's commitment to work-life balance. Additionally, Gridware provides a commuter allowance and company-paid training opportunities to help you grow in your career.

When answering, discuss specific projects where you designed data pipelines, the technologies you used, and how you managed scalability. Include metrics or improvements that resulted from your designs to showcase your impact.

Detail your experience with technologies such as Hadoop, Spark, or Kafka. Explain how you applied these tools to real problems, highlighting any challenges and the solutions you implemented.

Discuss the strategies you use to verify data quality, such as automated testing, validation checks, and monitoring in real-time. Illustrate with examples from previous roles to convey your systematic approach.

Share a specific project where collaboration was key. Discuss how you communicated with different team members and how you ensured that all data needs were met effectively.

Explain your understanding of data modeling concepts and detail your experience in designing efficient ETL processes. Mention any tools you've used and how it benefitted the overall system performance.

Provide an example of a workflow optimization you implemented, the methods you used, and the impact it had on performance. Be specific about the metrics you tracked to measure success.

Talk about specific issues such as data volume, velocity, or quality issues and how you addressed them. Providing a solution-focused mindset will showcase your problem-solving skills.

Share your strategies for professional development, such as attending conferences, following industry blogs, or participating in online courses. This shows your motivation to continuously learn and adapt.

Discuss critical data governance principles like compliance, data privacy, and security best practices. Provide insights into how you've implemented these principles in past projects.

Outline your systematic approach to troubleshooting; identify the problem, analyze logs, identify bottlenecks, and apply a structured resolution process. This highlights your analytical skills and proactive approach.