Design, implement, scale, and maintain backend systems that process large volumes of data.
Work on event-driven and API-based integrations.
Contribute to migration efforts toward a more domain-based and scalable architecture.
Build and optimize software for performance-sensitive workflows.
Investigate technical problems and propose solutions together with the team.
Collaborate closely with data science and engineering colleagues on technical solutions.
Participate in a collaborative development model where work is shared rather than handled alone.
Requirements
10+ years of backend software engineering experience, with strong technical depth.
We’re technology agnostic, so, you're more than welcome to switching your main language (Python, Scala, C/C++, Haskell, Elixir, Go, Ruby) to Java (core language)
Solid understanding of algorithms , data structures , and Big O notation.
Experience with Python and/or PySpark.
Experience building or maintaining complex, high-volume systems
Familiarity with heavy data processing tools and technologies such as Spark, Apache ecosystem tools, Delta Lake, Parquet, Kafka, and Avro.
Experience with Docker, SQL, and NoSQL databases.
Experience with REST APIs and event-driven integrations.
Comfortable working in performance-oriented, production-critical environments with high-throughput & low talency systems
Strong problem-solving skills and a proactive, collaborative working style.
Ability to communicate well with engineers and data science partners.
Background in computer science, computer engineering, or a related field is preferred.
Nice to Have Experience with AWS
Experience with Pandas.
Experience with Spring framework and microservices.
Experience working in large-scale data or analytics environments.