Senior Engineer, Data Platform

Role Overview

• Support the design and delivery of data ingestion pipeline and infrastructure
• Assist in the successful migration of legacy data lifecycle management to new platform without disrupting existing data consumers
• Establish and maintain SLIs and SLOs for new ingestion and data platform with dashboards and alerting to track performance
• Build flexible data storage layer supporting a variety of use cases, e.g., transactional, analytic, and machine learning workloads
• Implement comprehensive monitoring, observability, and incident response practices for all event data pipelines and services
• Collaborate with product engineering, analytics, and machine learning teams to define contracts, functional requirements, and standards
• Design and implement a semantic metadata layer that classifies and labels data assets across both products, enabling consistent data discovery, exposure policies, and identification of cross-product data reuse opportunities
• Architect and deliver a multi-tenant data model that supports secure data sharing and isolation across clients, with controls designed to meet regulatory and government compliance requirements

Requirements

• Deep understanding of data governance principles and data lifecycle management, including data quality, lineage, retention, and access control
• Strong familiarity with database backend technologies (OLAP vs. OLTP) and when to apply each, with hands-on experience using data warehouse technologies (Databricks, Clickhouse, Redshift, etc) at production scale
• Strong familiarity with SQL with the ability to write and optimize queries
• Skill at building complex systems and identifying core primitives and how to apply them to meet changing business needs and future roadmap requirements.
• Experience designing and operating data systems on a major cloud provider (AWS or GCP) and working in a multi-cloud deployment environment
• Proficiency with containerization and orchestration technologies, including Docker and Kubernetes
• Proven ability to integrate systems, connecting legacy platforms with modern architectures through well-designed interfaces and migration strategies
• Effective communicator who can facilitate system design discussions, document architectural decisions, and work across team boundaries
• (Nice to have) Familiarity with Elixir for building concurrent, fault-tolerant data services
• (Nice to have) Experience with data pipeline and streaming technologies such as Airflow, Kafka, Apache Flink, or similar
• (Nice to have) Hands-on experience with columnar/OLAP databases such as Databricks or ClickHouse
• Experience designing and operating data systems on AWS; GCP experience is a plus
• Strong collaboration and communication skills, comfortable leading design discussions, writing technical specs, and working across team boundaries
• Experience with Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or similar.

Tech Stack

• Airflow
• Amazon Redshift
• Apache
• AWS
• Cloud
• Docker
• Elixir
• Google Cloud Platform
• Kafka
• Kubernetes
• SQL
• Terraform

Benefits

• full range of medical, financial, and/or other benefits