Senior/Staff Data Engineer

As a Senior/Staff Data Engineer at StackAdapt, your main responsibilities will include designing modular and scalable real-time data pipelines, coordinating architectural improvements for our big data ML pipelines, and understanding custom ML algorithms in a low latency environment. You'll also work on microservice architectures that simultaneously run training, inference, and monitoring on numerous ML models. This role is integral in solving complex data challenges within our innovative digital advertising platform.

To qualify for the Senior/Staff Data Engineer position at StackAdapt, candidates should possess a deep understanding of algorithm and software design, concurrency, and data structures. A high GPA from a reputable Computer Science program or equivalent experience in a tech company is also required. Additionally, candidates should have experience in implementing machine learning algorithms and designing scalable distributed systems, making them a perfect fit for our data science team.

Yes, experience with machine learning is crucial for the Senior/Staff Data Engineer role at StackAdapt. You will be expected to implement custom ML solutions and design ML pipelines that efficiently process large datasets. Familiarity with probabilistic algorithms and a proven track record in ML applications will greatly benefit your contribution to our data science initiatives.

At StackAdapt, the work culture for a Data Engineer is highly collaborative, supportive, and inclusive. We believe in a friendly environment that encourages innovation and creativity. Our team members enjoy being part of a culture that values the diverse backgrounds and experiences of everyone, making for a stimulating workplace where ideas thrive and challenges are tackled together!

Absolutely! StackAdapt is a Remote First company, which means you have the flexibility to work from anywhere in the UK as a Senior/Staff Data Engineer. We understand the importance of work-life balance and provide our team with the tools and support to thrive in a remote setting.

It's essential to provide concrete examples of projects where you designed scalable data pipelines. Discuss the technologies you used, the challenges you faced, and how you overcame them. Highlight the impact your data pipelines had on the overall system performance and data throughput—making sure to relate your answer back to how those experiences align with the role at StackAdapt.

Express your familiarity with various machine learning algorithms and choose a couple that you can detail. Explain the problems you were solving, why you chose those algorithms, and how you implemented them. This will demonstrate your technical expertise and relevance to the Senior/Staff Data Engineer role at StackAdapt.

Explain your systematic approach to process optimization, such as identifying bottlenecks, analyzing performance metrics, and implementing changes gradually while testing their effectiveness. Providing a past scenario where you successfully optimized a process can reinforce your method and results to the interviewers at StackAdapt.

Discuss the big data tools and technologies you are comfortable with, such as Apache Hadoop, Spark, or Kafka. Elaborate on your experiences using these tools, how they fit into the workflow at previous positions, and how they can be integrated into StackAdapt's data architecture.

Share your understanding and experience with microservice architectures, including how you've deployed and maintained microservices in previous roles. Give concrete examples where this architecture benefited project agility and scalability, which are crucial for StackAdapt's data-driven initiatives.

Articulate your strategies for staying current, whether that be through online courses, attending conferences, or following thought leaders in the field. This reflects your commitment to continuous learning, which is essential in a rapidly evolving field like data engineering at StackAdapt.

This is an opportunity to highlight your problem-solving skills. Choose a specific instance, outline the complexity of the data challenge, your thought process in approaching it, and the final outcome. Emphasize how your solution brought value to the organization or team, which aligns with the innovative spirit of StackAdapt.

Discuss various strategies such as data partitioning, sharding, or indexing that you employ to manage and query large datasets efficiently. Relate these back to your previous experiences and how they can apply to the responsibilities you would have at StackAdapt as a Senior/Staff Data Engineer.

Share your experiences in communicating and collaborating in distributed settings, such as utilizing collaborative tools or participating in regular check-ins. Highlight the importance of clear documentation and active engagement in discussions, which promotes teamwork in remote configurations like StackAdapt's.

Craft a personalized response that expresses your enthusiasm for StackAdapt's innovative approach to digital advertising. Highlight specific elements of the company's culture, vision, and team dynamics that attract you, showcasing your alignment with StackAdapt's values and mission.