About the Role

We are looking for a curious and team-focused ODL Software Engineer to join our agile engineering team. In this role, you will be responsible for building and maintaining the data pipelines, services, and infrastructure that power our analytics and business intelligence platforms. This position is ideal for an engineer who is passionate about data, accountable for their work, and driven to create robust, scalable solutions.

What we are doing

The Operational Data Layer (ODL) team builds the platform that turns product activity into trusted, reusable data.

We partner with engineering teams across the company to help thememit Avro-based business eventsin a consistent, schema-governed way. Those events flow through ourstream and batch data platform processed withApache Flinkfor real-time pipelines andDatabricksfor scalable ELT and lakehouse workloads — before landing in datasets and services that downstream teams can rely on.

We also own thevisualization and data delivery layer: REST APIs and platform services that make curated data accessible to analytics, BI, and product teams. Our goal is to give teams a clear path from event emission to insight — with strong engineering standards around reliability, observability, and data quality.

As an Engineer, you will help shape this end-to-end architecture — from event contracts and pipeline design through to the services and platforms that expose data at scale — and mentor others on building durable, well-tested systems across the stack.

What our stack is

We work across event streaming, distributed processing, infrastructure automation, and service development:

Area

Technologies

Event contracts

Avro schemas, schema governance, business event emission

Stream processing

Apache Flink

Batch / lakehouse

Databricks, Spark

Services & APIs

Python (REST),



Kotlin / Spring Boot

Data tooling

SQL, Pandas, Jupyter Notebooks

Infrastructure

Terraform, CI/CD pipelines

Observability

Prometheus, Grafana, ELK (and related tooling)

Cloud & runtime

AWS / GCP / Azure, Docker, Kubernetes

Key Responsibilities

- Design, develop, and maintain efficient and reliableELT pipelines.
- Implement and manageCI/CD pipelinesto automate testing and deployment processes.
- UtilizeTerraformto manage and provision infrastructure as code.
- Develop comprehensive tests (Test Development) to ensure data quality and system reliability.
- Contribute to efficient and reliable pipelines to transform raw data into data that can be consumed by users and services.
- Ensure data quality across the Data Lake, ensuring data and transformation errors are identified and resolved quickly
- Contribute to the development and maintenance ofBI Dashboardingsolutions.
- Work within a team-focused environment, demonstrating curiosity and a data-driven mindset.

Required Qualifications

- 3+ years of experience in a software or data engineering role.
- Solid programming skills inPython.
- Experience building or consumingREST services.
- Hands-on experience with a distributed data processing framework likeSpark/Databricks.
- Familiarity withCI/CDprinciples and tools.
- Basic understanding of data science tools and techniques (SQL, Jupyter Notebooks).
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

- Experience withCloud platforms (AWS, GCP, Azure).
- Knowledge of containerization technologies likeDockerandKubernetes (K8s).
- Familiarity withobservabilitytools for monitoring and logging.
- Experience with Infrastructure as Code, particularlyTerraform.
- Experience buildingREST services in Python or Kotlin

📌 Engineer 2 (Noida)
🏢 Anaplan
📍 Noida