Sr. Software Development Engineer

iSpot

4d•$136,100 - $174,210•Hybrid

About The Position

Are you ready to revolutionize the way we track and analyze data? We're looking for a talented Senior Software Engineer to join our team and make a significant impact. You will thrive at the intersection of complex data science and robust software architecture, helping us turn high-level methodology into high-performance reality. We value engineers who take total ownership of their work, from the initial architectural logic to the ultimate quality and integrity of the data it produces.

Requirements

Core Engineering: Strong professional experience in either Java or Python, with the versatility to work across both as required by the stack.
Data Processing: Proven experience with Apache Spark for large-scale data manipulation.
Modern Data Stack: Proficiency with SQL and experience navigating environments involving Snowflake, MySQL, and AWS-based data lakes (S3, Glue, Iceberg).
AI-Augmented Workflow: Experience leveraging AI tools like Kiro to optimize coding workflows, documentation, and automated testing.

Nice To Haves

Data Domain Knowledge: Experience with Data Clean Rooms, DMPs (LiveRamp, Neustar), or Data Science (R) is a plus.
Strong Collaboration: You are a "People First" engineer who builds understanding through active listening and working seamlessly across disciplines.
Direct Impact: You thrive when given the autonomy to solve hard problems and the opportunity to influence the direction of the product.
Navigating Ambiguity: You thrive in complex environments, knowing how to admit what you don't know and partnering with the right people to find the answer.
Sustainable Excellence: You advocate for best practices in software development—from code reviews to CI/CD—ensuring speed is a byproduct of quality.
Leadership by Example: You set a high ethical bar for data privacy and security. You view production incidents as blameless learning opportunities and always anticipate what’s next for the product.

Responsibilities

Project Lifecycle Leadership: Drive high-priority projects from initial system design and technical scoping through to final release and post-launch optimization.
Architectural Influence: Take a seat at the table during the earliest stages of product development to ensure technical feasibility, scalability, and long-term maintainability.
Methodology Translation: Partner with Data Science teams to translate sophisticated theoretical models and algorithms into scalable, production-grade code.
Tackle Big Data: Architect and maintain systems to process, match, and store large datasets from diverse internal and third-party sources.
End-to-End Quality: Take responsibility for the entire lifecycle of your features—from robust unit and route testing to ensuring long-term data quality and accuracy.
Enhance Visibility: Integrate monitoring and observability tools to boost application performance and ensure system reliability.
Optimize Performance: Analyze and design improvements to scale our infrastructure and data pipelines as our data footprint grows.
Break Down Complexity: Dissect business requirements and transform them into manageable, well-defined engineering tasks.
Drive Team Success: Contribute to shared goals within a cross-functional Agile team, fostering a culture of technical excellence and psychological safety.
Mentorship & Growth: Guide and sponsor other engineers, helping them navigate technical challenges and grow their careers through clear, supportive feedback.