About the Role

We are seeking an experienced and accountable Senior ODL Software Engineer to provide technical leadership for our data engineering initiatives. In this role, you will architect and lead the development of our core data infrastructure. You will mentor other engineers, drive best practices, and collaborate with stakeholders to build data-driven solutions. This is a key role for a data-centric leader who is passionate about building scalable systems and fostering a culture of curiosity and accountability.

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 and Databricks for 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 a Senior 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

- Lead the architecture, design, and implementation of complexELT pipelinesand data processing systems across Flink and Spark/Databricks.
- Own the strategy and execution ofCI/CD pipelinesandTerraforminfrastructure to ensure resilient and automated deployments.
- ChampionTest Developmentbest practices and mentor junior engineers on creating effective testing strategies.
- Build 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
- Drive the vision and technical roadmap forBI Dashboardingand data delivery platforms.
- Mentor and guide other engineers, promoting a team-focused and data-driven culture.
- Take accountability for the overall health, performance, and scalability of our data systems.

Required Qualifications

- 5+ years of experience in software and data engineering, with a proven track record of technical leadership.
- Expert-level programming skills inPython.
- Extensive experience withSpark/Databricksor other distributed data processing frameworks.
- Proven success in designing, building, and maintaining automatedCI/CD pipelines.
- Strong experience withTerraformfor infrastructure automation.
- AdvancedData Sciencetoolkit experience (SQL, Jupyter Notebooks).
- Experience mentoring engineers and leading complex technical projects.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

- Deep experience withCloud platforms (AWS, GCP, Azure)and designing cloud-native solutions.
- Deep experience designing and building scalableREST services in Python or Kotlin (Springboot)
- Solid understanding ofKubernetes (K8s)andDockerin a production environment.
- Experience implementing modernobservabilitystacks (e.g., Prometheus, Grafana, ELK).
- Experience building data platforms or frameworks from the ground up.

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