Staff Data Platform Engineer

Machinify • Roseville, CA

13d • $220,000 - $230,000 • Remote

About The Position

We are seeking an experienced Staff Data Platform Engineer with a focus on big data systems, orchestration, and ETL processes. In this role, you will architect and implement scalable data infrastructure using both existing and greenfield systems. You will collaborate with cross-functional teams to ensure our data solutions meet business needs and leverage cloud-native tools for optimal performance.

Requirements

• 7+ Years in software development with Python and SQL.
• Strong understanding of ETL processes, big data pipelines, and relational databases (PostgreSQL, SQL Server, etc.).
• Experience with orchestration tools (e.g., Airflow, Prefect, Dagster).
• Knowledge of cloud platforms (AWS, Azure, GCP) and their ecosystem tools.
• Strong problem-solving skills and clean coding practices.
• Experience with Apache Spark or similar technologies.
• Experience with agentic coding workflows.
• Experience with data modeling, transformation, and integration.
• Experience with data quality, lineage, and modeling tools.

Nice To Haves

• Experience in software development with Golang.
• Experience with managed data lake systems (e.g., Databricks, Snowflake, AWS Redshift).
• Familiarity with Kubernetes and container orchestration (Docker, Helm, etc.).
• Familiarity with infrastructure-as-code systems (e.g., Terraform, Ansible)
• Knowledge of monitoring and logging tools for distributed systems (Prometheus, Grafana, ELK stack).
• Experience with CI/CD pipelines and automated testing.
• Strong understanding of data modeling, ETL workflows, and data transformation techniques.

Responsibilities

• Develop scalable and observable data platforms tailored to business needs.
• Build and manage systems in cloud environments using AWS and Azure.
• Collaborate with data scientists, engineers, and experts to deliver right-fit solutions while increasing data quality and ease-of-use.
• Ensure data systems are reliable, flexible, and scalable for large datasets from diverse sources (batch vs event, on-prem vs cloud, etc)
• Architect and build reusable data pipeline and DAG systems.
• Create and deploy Kubernetes-based systems in cloud-native environments.
• Support machine learning workflows through data modeling and transformation.

Benefits

• PTO, Paid Holidays, and Volunteer Days
• Eligibility for health, vision and dental coverage, 401(k) plan participation with company match, and flexible spending accounts
• Tuition Reimbursement
• Eligibility for company-paid benefits including life insurance, short-term disability, and parental leave.
• Remote and hybrid work options

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees