Senior Software Engineer - Data Infrastructure
New
A
ApartmentIQRentals Industry
U.S. from coast to coastFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonRuby on RailsAirflowdbtAWS Lambda
Requirements
- 5+ years of software or data engineering experience with a focus on delivering pipelines that power customer-facing features.
- Strong experience in Ruby on Rails.
- Strong experience in Python.
- Deep understanding of large-scale data collection, including web scraping, parsing, proxy management, and structured feed ingestion.
- Hands-on experience with batch-style data workflows using tools like dbt, Airflow, or similar equivalents.
- Deep expertise in AWS infrastructure (RDS, ECS, S3, Lambda, OpenSearch).
- Familiar with modern stacks for performance tracking, error monitoring, and distributed tracing.
- Strong ability to translate complex technical details into clear, actionable product outcomes.
- Experience navigating a fast-paced, growth-stage environment where priorities shift and ownership is expected.
Responsibilities
- Deliver Product-Focused Data: Own the end-to-end delivery of data across Market Research, Market Surveys, and Daylight Revenue, aligning technical priorities with product goals.
- Scale Data Ingestion: Design and evolve our ingestion pipelines, processing data for 10M+ multifamily units through XML/JSON feeds, web scraping, warehouse transformations, and API exposure.
- Set Technical Standards: Define what accuracy, completeness, and timeliness mean for our datasets, ensuring all requirements meet the specific needs of each product line.
- Collaborate Across Teams: Work closely with Product and Application Engineering to ensure new datasets unlock measurable features and actionable customer insights.
- Ensure Operational Excellence: Build strong observability into our systems, including daily monitoring, anomaly detection, and automated alerts to maintain ingest health.
- Manage Roadmap Execution: Lead the delivery of data milestones by defining goals, tracking progress in Linear, and communicating outcomes to stakeholders.
- Adopt Emerging Tools: Stay current with data and AI tooling to help the team work more efficiently and integrate new technologies where they add value.
- Document & Share Knowledge: Foster a culture of continuous improvement by maintaining clear documentation and mentoring others on data best practices.
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