Senior Data Platform Engineer

About The Role

The Data Platform Engineer is responsible for enabling data practitioners such as data engineers, business analysts and data scientists to self-serve on a robust and scalable platform infrastructure by designing and building the right tools and reusable data platform frameworks.

In This Role, You Will

• Design, develop, and maintain the storage, processing, orchestration, cataloging and governance components of a scalable and secure data platform.
• Build the tools, libraries, and services that allow other teams to own and manage their own pipelines and workflows independently.
• Provide self-service infrastructure (e.g., templates, SDKs, CI/CD patterns, DBT macros) to support repeatable and consistent data engineering practices.
• Implement and manage data platform components: orchestration frameworks, data catalog, access control layers, and metadata systems.
• Collaborate with stakeholders to define SLAs, monitoring, and observability across the data stack.
• Champion infrastructure as code, automation, and standardization across the platform.
• Ensure data security, compliance, and cost efficiency across environments.
• Mentor and guide other data platform associates with solutioning, code reviews and best practices adoption.

Minimum Qualifications:We realize applying for jobs can feel daunting at times. Even if you don’t check all the boxes in the job description, we encourage you to apply anyway.

• 6+ years of experience in Data/Infrastructure Engineering, with at least 3 years focused on building self-service platforms.
• Proficiency in Python, SQL and experience building reusable templates and frameworks.
• Deep understanding of cloud data resources in AWS (S3, EKS, Glue, Athena etc.).
• Expertise in building and supporting solutions on Snowflake.
• Experience in setting up integrations or connecting tools (for e.g. Snowflake - Power BI, Snowflake - AWS services etc.)
• Hands-on experience with orchestration frameworks (Airflow, Prefect etc.).
• Experience with distributed systems and data processing frameworks (e.g., Apache Spark).
• Comfortable building and debugging CI/CD, infrastructure as code (Terraform), and GitOps practices.
• Familiarity with Kubernetes, Docker, and container-based deployment models.
• Demonstrated capability in security & governance: RBAC, masking, SSO (Okta), secrets management and audit logging.

What Can Help Your Application Stand Out

• Experience in Data Science productionisation (MLOps).
• Active contributions to open-source data projects.
• Experience implementing Apache Iceberg for open-table formats.
• Experience implementing Kafka, Kinesis, or Flink for streaming architectures.
• Exposure to observability tools (Datadog, splunk etc.).

Our Commitment to Inclusivity and Diversity

At G2, we are committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran, or physical or mental disability status. Learn more about our commitments here.

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