Senior Backend Engineer

Responsibilities:

Design, develop, test, and maintain production-grade services and data pipelines using Python and Go.

Build and manage Apache Airflow/MWAA DAGs, custom operators, sensors, integrations, and workflow orchestration.

Develop Databricks and PySpark jobs for large-scale data processing, transformation, validation, and analytics.

Design reliable ETL/ELT pipelines for customer, order, product, campaign, event, and marketing data.

Build REST APIs, backend services, microservices, and platform capabilities using appropriate frameworks and design patterns.

Develop and maintain AWS-based solutions using services such as S3 Lambda, MWAA, Glue, Redshift, SQS, Secrets Manager, ECS, and related services.

Build event-driven systems using Kafka, SQS, Redis, and other messaging or caching technologies.

Design data models and work with PostgreSQL, MySQL, Redshift, Redis, and other relational or non-relational data stores.

Integrate internal systems and external marketing platforms such as Facebook, Google, CleverTap, Mixpanel, AppsFlyer, Google Analytics, and Netcore.

Write clean, maintainable, secure, and scalable code with appropriate error handling, retries, idempotency, and observability.

Improve the performance, reliability, availability, and cost efficiency of existing services and pipelines.

Implement automated testing, code reviews, monitoring, logging, tracing, and production support practices.

Participate in system design discussions and contribute to technical decisions and architecture.

Work with DevOps and platform teams to improve CI/CD, deployment automation, and infrastructure reliability.

Collaborate with cross-functional teams to understand requirements and deliver pragmatic technical solutions.

Contribute to engineering standards, documentation, reusable components, and mentoring of junior engineers.

Requirements:

4+ years of professional software engineering experience.

Strong proficiency in Python and/or Go, with experience delivering production systems.

Good understanding of data structures, algorithms, object-oriented design, concurrency, and operating-system fundamentals.

Hands-on experience building data pipelines, backend services, APIs, or distributed systems.

Practical experience with Apache Airflow, workflow orchestration, or equivalent scheduling platforms.

Experience with Databricks, PySpark, Spark, Delta Lake, or large-scale data processing.

Strong SQL skills and experience with PostgreSQL, MySQL, Redshift, or similar databases.

Experience with AWS services, especially S3 Lambda, MWAA, Glue, Redshift, SQS, Secrets Manager, ECS, or related services.

Experience with Kafka, Redis, or other streaming, messaging, and caching systems.

Understanding of REST APIs, microservices, asynchronous processing, and event-driven architecture.

Experience with Git and collaborative development practices such as pull requests and code reviews.

Experience writing unit, integration, and end-to-end tests.

Knowledge of CI/CD tools and deployment practices using Jenkins, GitHub Actions, Docker, or similar technologies.

Understanding of application and data security, access control, secrets management, privacy, and data protection.

Strong analytical and problem-solving skills.

Ability to independently own features or services from design through production deployment.

Strong communication skills and the ability to collaborate effectively across teams.