Senior Software Engineer, Data Engineering

Todyl • Atlanta, GA

27d • $170,000 - $190,000 • Hybrid

About The Position

The Data team at Todyl builds and operates systems that turn high-volume security telemetry into data that the platform, partners, AI/ML teams, and product teams can use. The platform ingests terabytes of security telemetry each day through a Kafka-compatible streaming layer into Quickwit and ClickHouse. This is a data infrastructure role focused on ingestion pipelines, storage, search, analytics, and business intelligence—not an application-database role.

This is a senior individual contributor position on a small team. Working with the Staff data engineer who sets the team’s technical direction, the engineer will own significant parts of the ingestion and storage systems end to end, become a subject-matter expert in an area of the platform, and take ambiguous projects through production stabilization and long-term maintenance. The role offers influence over technical decisions and scope to grow as the team expands.

The successful candidate is a proactive technical expert who makes sound architecture decisions, designs for failure and scale, builds in monitoring and debugging, and owns systems throughout their lifecycle. They mentor engineers, lead design reviews, communicate technical work and business impact clearly, and actively use AI tools in day-to-day development. They should be comfortable adapting systems to changing requirements in a fast-paced startup environment.

The position uses a collaborative hybrid work model, with offices in Denver’s LoDo neighborhood, Midtown Atlanta, and Augusta, Georgia. The stated salary range is $170,000–$190,000, plus equity.

Requirements

• At least 5 years of software engineering experience, including at least 2 years building and operating data infrastructure in production.
• Production experience with a streaming platform such as Kafka, Redpanda, Kinesis, or a similar log-based system.
• Experience building or operating producers and consumers and handling consumer lag.
• Production experience with at least one search or analytics store, such as ClickHouse, Elasticsearch, OpenSearch, or Quickwit.
• Experience designing indexes or tables and tuning slow queries.
• Strong Go or Python skills and strong SQL skills.
• Demonstrated experience owning complex data features or projects end to end, through production and long-term maintenance.
• Experience with high data volumes and ability to explain the cost and performance trade-offs made.
• Ability to actively use AI tools in day-to-day work.
• Ability to mentor engineers, lead design reviews, communicate technical concepts to technical and non-technical stakeholders, and explain the business impact of technical work.
• Comfort working in a fast-paced startup environment and adapting existing systems to changing requirements.

Nice To Haves

• Experience with Quickwit specifically.
• Experience with columnar formats and object storage, such as Parquet, Iceberg, and S3.
• Experience with log shippers such as Vector or Fluent Bit.
• Experience with observability for data systems, such as Grafana and Prometheus.
• Experience with multi-tenant SaaS, AWS, and Linux.
• Security telemetry or SIEM experience.

Responsibilities

• Design and implement scalable, reliable, and fault-tolerant data ingestion pipelines from multiple sources through Kafka-compatible streaming into Quickwit and ClickHouse for real-time analytics, search, and visualization.
• Own complex features and projects from ambiguous problem statements through implementation, production stabilization, and long-term maintenance; break work into milestones and estimate large epics.
• Design and tune storage systems, including indexes, tables, partitioning, retention, and query performance, balancing cost, scale, security, and maintainability; document designs for future reference.
• Build monitoring, alerting, and debugging into systems to detect correctness and data freshness issues early and reduce detection and resolution time.
• Participate in the team’s on-call rotation, resolve most issues independently, and follow up on incidents and resulting toil.
• Partner with AI/ML and product teams during system design and provide fast, correct queries to teams that depend on the data.
• Mentor engineers through pairing, design partnership, and code review, and lead thorough design reviews.
• Proactively reduce technical debt across multiple projects each year and initiate important unassigned work.
• Use code review and testing to improve quality; design testable systems with comprehensive coverage, identify testing gaps, and verify changes after release using dashboards and logs.
• Run retrospectives, follow through on findings, document patterns, and create onboarding materials.
• Actively use AI tools, including tools such as Claude, to accelerate development, reduce toil, and solve data engineering problems.

Benefits

• Employee equity program.
• Medical, dental, and vision insurance options.
• Unlimited paid time off.
• 401(k) plan.
• Paid parental leave.
• Hybrid work environment with offices in Denver’s LoDo neighborhood, Midtown Atlanta, and Augusta, Georgia.
• Parking and public transportation commuter benefits.
• Professional growth and development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed