Lead Software Engineer - Python/Data Pipelines
Colossus Technologies GroupAbout the role
We’re working with a Series A, cybersecurity startup that is looking for a Lead Software Engineer to join its engineering team. This is a hands-on engineering role for someone who enjoys solving complex technical problems, designing scalable systems, and building large-scale data pipelines from the ground up. The environment is heavily Python-based, and this person will contribute directly to both architecture and production code while helping mentor other engineers.
Responsibilities:
Design and build large-scale data pipelines from scratch, taking ownership from initial architecture through production deployment.
Build systems that ingest, process, transform, and analyze large volumes of data from multiple sources.
Own complex backend engineering problems end-to-end.
Break large technical challenges into manageable components and drive them through implementation.
Design scalable, reliable backend systems and make thoughtful architectural decisions.
Write production Python and contribute to a backend environment built heavily around Django and FastAPI.
Identify performance bottlenecks, scalability concerns, and data quality issues.
Improve the reliability, maintainability, and performance of existing systems.
Mentor junior engineers and contribute to engineering best practices.
Required Skills:
Strong professional Python development experience.
Experience with Django and/or similar Python backend frameworks.
Demonstrated experience designing and building data pipelines from the ground up.
Experience working with large or complex datasets and production data-processing systems.
Experience with high-volume ingestion, ETL/ELT, streaming, or event-driven data architectures.
Experience with technologies such as Kafka, Spark, Airflow, or similar data-processing/orchestration platforms.
Data quality, validation, or observability experience
Strong systems design and software engineering fundamentals.
Experience designing scalable backend or distributed systems.
Practical understanding of algorithms and data structures.
Ability to independently own complex technical projects from design through production.
Experience mentoring or providing technical guidance to other engineers.
Responsibilities
- Design and build large-scale data pipelines from scratch, taking ownership from initial architecture through production deployment.
- Build systems that ingest, process, transform, and analyze large volumes of data from multiple sources.
- Own complex backend engineering problems end-to-end.
- Break large technical challenges into manageable components and drive them through implementation.
- Design scalable, reliable backend systems and make thoughtful architectural decisions.
- Write production Python and contribute to a backend environment built heavily around Django and FastAPI.
- Identify performance bottlenecks, scalability concerns, and data quality issues.
- Improve the reliability, maintainability, and performance of existing systems.
Qualifications
- Strong professional Python development experience.
- Experience with Django and/or similar Python backend frameworks.
- Demonstrated experience designing and building data pipelines from the ground up.
- Experience working with large or complex datasets and production data-processing systems.
- Experience with high-volume ingestion, ETL/ELT, streaming, or event-driven data architectures.
- Experience with technologies such as Kafka, Spark, Airflow, or similar data-processing/orchestration platforms.
- Data quality, validation, or observability experience.
- Strong systems design and software engineering fundamentals.
Skills mentioned
About Colossus Technologies Group
At Colossus Technologies Group, we provide top-tier cybersecurity and digital trust staffing, IT consulting, and project management solutions, including privacy, security, and GRC SaaS platform solution implementation. Our expertise ensures businesses have access to the right talent and strategies to safeguard their digital assets, optimize operations, minimize and govern digital risks and drive growth.