Senior Software Engineer, Backend (Central/Eastern Time)

RocketReach

2d•$170 - $200•Remote

About The Position

We’re looking for a Backend Engineer to join the Core Data Team who thrives in data-intensive environments and can build scalable systems. This role combines backend engineering and data infrastructure. You’ll work on systems that process large datasets, power APIs, and transport data reliably to customers. You should be comfortable operating with real production constraints—performance, cost, and imperfect data—and making sound engineering tradeoffs. The salary range for this role is $170-200k.

Requirements

Have 5+ years of professional backend engineering experience
Are located in the Central or Eastern time zones
Are proficient in Python
Have strong SQL skills
Have experience working with large datasets
Have experience building or maintaining data pipelines or backend systems at scale
Are familiar with REST API best practices
Have experience with ORMs (e.g., Django, SQLAlchemy)
Have experience with AWS services (Redshift, Fargate, S3, RDS, IAM, OpenSearch, DynamoDB)
Have strong communication and interpersonal skills

Nice To Haves

Experience working in small, high-autonomy engineering teams
Experience with database performance tuning and maintenance (e.g., autovacuum, bloat control, transaction wraparound)
Experience in email verification systems
Familiarity with Terraform
Experience with workflow orchestration tools (e.g., Airflow, AWS Step Functions)

Responsibilities

Design and build distributed systems that process billions of events per day
Build performant, reliable APIs that support thousands of customer applications and integrations
Develop and maintain customer-specific solutions, ensuring SLA commitments are met
Build and maintain data pipelines (ETL, batch processing, enrichment workflows)
Work with large datasets across systems like S3, Redshift, PostgreSQL, and DynamoDB
Optimize SQL queries and data access patterns for performance and cost efficiency
Develop processes for cleaning and enriching large-scale datasets
Analyze algorithms, models, and LLMs for quality, performance, and cost tradeoffs
Collaborate closely with product and data teams to ship features quickly and iteratively