About the Role

We seek an experienced and highly skilled Senior Data Platform Engineer to join our dynamic team. In this crucial role, you will be responsible for designing, building, and maintaining our organization's data platforms and infrastructure, ensuring efficient and reliable data processing, storage, and analysis capabilities. Your expertise in data engineering will contribute to our organization's data-driven decision-making and overall success.  

You Will

• Architect and build scalable and performing data platforms by leveraging technologies like Apache Spark, Elastic, Kafka, Kubernetes, and various cloud-based data services.
• Design and develop data pipelines for ingesting, transforming, and processing large volumes of structured and unstructured data from multiple sources.
• Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and translate them into robust and efficient scalable data solutions.
• Optimize data workflows and processes for performance, reliability, and cost-effectiveness.
• Implement data governance policies, data quality controls, and data security measures to ensure data integrity and compliance with regulatory requirements.
• Automate and streamline data operations through scripting, containerization, and orchestration tools.
• Participate in code reviews, knowledge sharing, and mentoring of junior team members.
• Stay up-to-date with emerging data technologies, trends, and best practices, and contribute to the continuous improvement of our data platform.

You Have

• Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
• Minimum of 5 years of experience in data engineering or a related role, with a strong focus on building and maintaining data platforms and infrastructure.
• Proficient in programming languages such as Python, Scala, or Java, and experience with SQL and NoSQL databases.
• Hands-on experience in distributed computing frameworks like Apache Spark, Ray, and related ecosystem tools.
• Experience cloud platforms (e.g., AWS, GCP, Azure) and their data services.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience in solving complex problems using both structured and unstructured data.
• Strong understanding of data modeling, data warehousing, and data integration concepts.
• Excellent problem-solving, analytical, and troubleshooting skills.
• Ability to work collaboratively in a team environment and communicate complex technical concepts effectively.

Nice to Have

• Master's degree in a relevant field or equivalent experience.
• Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).
• Experience in data governance, data quality, and data security best practices.
• Experience in agile software development methodologies and DevOps practices.
• Experience with machine learning and data science workflows is a plus.

In this role, you will play a critical part in shaping our data infrastructure and ensuring that data is available, reliable, and ready for analysis. Your expertise in data engineering will contribute to our organization's data-driven decision-making and overall success.

Compensation

$170,000 - $230,000

Message to applicants applying to work in the U.S.:

When available, the salary range posted for this position reflects the projected hiring range for new hire salaries in U.S. locations. For non-sales roles, the hiring ranges reflect base salary and do not include bonuses, equity, or benefits. Hiring ranges for sales positions include base and incentive target, and do not include equity or benefits. Individual pay is determined by the candidate's hiring location and additional factors, including but not limited to skillset, experience, and relevant education, certifications or training. Applicants may not be eligible for the full salary range based on their U.S. hiring location. The recruiter can share more details about compensation for the role in your location during the hiring process.