We are seeking a highly skilled Senior Software Engineer to join our team responsible for large‑scale data processing, distributed computation, and performance‑critical backend services.
This role is ideal for an experienced backend engineer with a strong Python background who has built and optimized data pipelines at scale.You will design, build, and optimize systems that process large volumes of data using technologies such as Python, Databricks, and modern cloud‑native tooling.
This is a senior technical position where architectural thinking, hands‑on coding ability, and ownership of end‑to‑end data workflows are essential.
Responsibilities:
Design, develop, and maintain scalable, high‑performance backend services in Python.
Build and optimize large‑scale data processing pipelines running on Databricks.
Implement efficient algorithms and data transformations to support analytical and operational needs.
Optimize performance, throughput, and reliability of distributed data workflows.
Collaborate closely with Data Scientists, Product Managers, and other engineering teams to translate requirements into scalable solutions.
Implement monitoring, alerting, and observability for data workloads.
Ensure code quality through best practices such as code reviews, testing, CI/CD, and documentation.
Contribute to architectural decisions and technical strategy for the data platform.
Troubleshoot production issues, perform root‑cause analysis, and optimize system stability.
This role is ideal for an experienced backend engineer with a strong Python background who has built and optimized data pipelines at scale.You will design, build, and optimize systems that process large volumes of data using technologies such as Python, Databricks, and modern cloud‑native tooling.
This is a senior technical position where architectural thinking, hands‑on coding ability, and ownership of end‑to‑end data workflows are essential.
Responsibilities:
Design, develop, and maintain scalable, high‑performance backend services in Python.
Build and optimize large‑scale data processing pipelines running on Databricks.
Implement efficient algorithms and data transformations to support analytical and operational needs.
Optimize performance, throughput, and reliability of distributed data workflows.
Collaborate closely with Data Scientists, Product Managers, and other engineering teams to translate requirements into scalable solutions.
Implement monitoring, alerting, and observability for data workloads.
Ensure code quality through best practices such as code reviews, testing, CI/CD, and documentation.
Contribute to architectural decisions and technical strategy for the data platform.
Troubleshoot production issues, perform root‑cause analysis, and optimize system stability.
Requirements:
5+ years of backend software engineering experience, with a strong focus on Python.
Hands-on experience with Apache Spark, Databricks, or similar distributed-processing frameworks.
Proven ability to design and optimize high-scale data pipelines handling large datasets.
Strong understanding of distributed systems, parallel processing, and performance tuning.
Familiarity with cloud environments (Azure, AWS, or GCP).
Experience with modern CI/CD processes, testing frameworks, and code-quality standards.
Strong understanding of data structures, algorithms, and system design.
Excellent problem-solving skills and ability to work independently.
Nice-to-Have Skills
Experience in data lakehouse architectures or cloud‑native data platforms.
Familiarity with container technologies (Docker, Kubernetes).
Background in cybersecurity, analytics platforms, or large-scale SaaS systems.
Hands-on experience with AI concepts, LLMs, and agents.
5+ years of backend software engineering experience, with a strong focus on Python.
Hands-on experience with Apache Spark, Databricks, or similar distributed-processing frameworks.
Proven ability to design and optimize high-scale data pipelines handling large datasets.
Strong understanding of distributed systems, parallel processing, and performance tuning.
Familiarity with cloud environments (Azure, AWS, or GCP).
Experience with modern CI/CD processes, testing frameworks, and code-quality standards.
Strong understanding of data structures, algorithms, and system design.
Excellent problem-solving skills and ability to work independently.
Nice-to-Have Skills
Experience in data lakehouse architectures or cloud‑native data platforms.
Familiarity with container technologies (Docker, Kubernetes).
Background in cybersecurity, analytics platforms, or large-scale SaaS systems.
Hands-on experience with AI concepts, LLMs, and agents.
This position is open to all candidates.
