Data Platform Engineer: Pipelines, Governance & Cloud

movableink; United States; Remote; USD 91,000 - 116,000; Full time

Benefits offered by this job

Elixir

Airflow

Kafka

Flink

Databricks/ClickHouse

Job summary

Movable Ink seeks a Senior Data Platform Engineer to help build and modernize a shared data platform. You’ll design ingestion pipelines, support multi-cloud deployments, and ensure governed access for engineering, analytics, and ML teams.

The role emphasizes collaboration across product engineering, analytics, and ML teams, with a focus on data governance, scalability, and reliable data services for diverse workloads.

Qualifications

• Ability to learn new technologies while keeping product and end-user needs in view.
• Knowledge of data governance and lifecycle practices, including quality, lineage, retention, and access control.
• Familiarity with OLTP and OLAP databases, production data warehouse systems, and SQL query writing and optimization.

Responsibilities

• Design and deliver data ingestion pipelines and infrastructure.
• Migrate legacy data lifecycle processes to a newer platform while maintaining service for existing consumers.
• Set and track service indicators and dashboards.
• Build storage for transactional, analytical, and ML workloads.
• Improve monitoring, observability, and incident response for data pipelines and services.
• Collaborate across product engineering, analytics, and ML to define requirements, contracts, and standards.
• Develop metadata to classify data assets, clarify exposure policies, and identify reuse opportunities.
• Contribute to multi-tenant data models that support secure sharing and client isolation.

Skills

Learning new technologies

Data governance

SQL optimization

Cross-team collaboration

System design communication

Tools

Docker

Kubernetes

Job description

Movable Ink seeks a Senior Data Platform Engineer to help build and modernize a shared data platform. You’ll design ingestion pipelines, support multi-cloud deployments, and ensure governed access for engineering, analytics, and ML teams.

The role emphasizes collaboration across product engineering, analytics, and ML teams, with a focus on data governance, scalability, and reliable data services for diverse workloads.