Platform Engineer III
Role details
Job location
Tech stack
Job description
As a Data Platform Engineer III (Senior), you will design, build, and operate the foundational infrastructure that powers data-driven decisions across the organization. You will own complex technical problems end-to-end -- from architecture and implementation to operations and reliability -- while mentoring junior engineers and influencing cross-team technical strategy.
You will collaborate closely with analytics, machine learning, and product teams to evolve the platform to meet growing scale, compliance, and quality requirements. This is a high-impact, high-autonomy role for engineers who care deeply about data reliability, developer experience, and scalable system design., Platform Architecture & Engineering
- Design and implement scalable, reliable, and cost-efficient data platform components, including ingestion pipelines, storage layers, orchestration frameworks, and serving infrastructure.
- Lead architectural decisions for data systems, evaluate trade-offs, and document technical decisions (ADRs) for broader team alignment.
- Own the full lifecycle of platform components: design, build, test, deploy, monitor, and optimize.
- Drive adoption of platform-as-a-product principles, ensuring internal teams have self-service tooling, clear SLAs, and well-documented APIs.
Data Reliability & Quality
- In collaboration with the data governance team, implement and maintain data observability tooling (data quality checks, anomaly detection, lineage tracking) to ensure trust in data assets.
- Define and enforce SLAs/SLOs for data pipelines and platform services; own incident response and root-cause analysis for platform-related outages.
- Establish and improve testing practices for data pipelines (unit, integration, and contract testing).
Infrastructure & Operations
- Manage cloud data infrastructure (AWS, GCP, or Azure) using infrastructure-as-code tools such as Terraform, Pulumi, or CDK.
- Optimize platform cost, performance, and scalability through profiling, benchmarking, and capacity planning.
- Build and maintain CI/CD pipelines for data platform components; enforce engineering best practices (code review, versioning, documentation).
Collaboration & Technical Leadership
- Serve as a technical anchor for platform squads; mentor Level I and II engineers through code reviews, pairing sessions, and design feedback.
- Partner with data engineering, ML engineering, and analytics teams to understand requirements and translate them into platform capabilities.
- Represent the data platform team in cross-functional planning; contribute to roadmap prioritization and estimation.
- Contribute to and help maintain internal engineering standards, runbooks, and on-call practices.
Requirements
- 5-8 years of professional software or data engineering experience, with at least 3 years focused on data platform, infrastructure, or distributed systems.
- Strong proficiency in Python and/or Scala/Java for building data pipelines and platform tooling.
- Deep working knowledge of a modern data warehouse or lakehouse platform (Redshift, Snowflake, BigQuery, Databricks, or similar).
- Experience with workflow orchestration tools such as Apache Airflow, Prefect, or Dagster.
- Solid understanding of cloud infrastructure (AWS, GCP, or Azure) and infrastructure-as-code (Terraform or equivalent).
- Experience designing and building streaming and batch data pipelines at scale (Kafka, Kinesis, Pub/Sub, or equivalent).
- Proven ability to own complex systems end-to-end with minimal oversight; demonstrated technical judgment and decision-making.
- Strong communication skills; ability to explain technical concepts to non-technical stakeholders and write clear design documents.
Preferred Qualifications
- Knowledge of data modeling concepts (Kimball, Data Vault, OBT) and semantic layer frameworks (dbt, LookML).
- Experience with containerization and orchestration (Docker, Kubernetes, Helm).
- Background in ML infrastructure or MLOps (feature stores, model registries, training pipelines).
- Exposure to data governance, privacy engineering, or regulatory compliance (HIPAA).
- Prior experience leading technical projects or acting as a tech lead on a data platform team.
Open-source contributions to data tooling or active participation in the data engineering community
Education: Minimum of HS Diploma or GED Bachelors preferred
Benefits & conditions
Team Member Benefits
- Medical, Dental, Vision, Prescription Coverage (22.5 hours per week or above for full-time and part-time team members)
- Life & AD&D Insurance.
- Short-Term and Long-Term Disability (with options to supplement)
- 403(b) Retirement Plan: Employer match, additional non-elective contribution
- PTO & Paid Sick Leave
- Tuition Assistance, Advancement & Academic Advising
- Parental, Adoption, Surrogacy Leave
- Backup and On-Site Childcare
- Well-Being Rewards
- Employee Assistance Program (EAP)
- Fertility Benefits, Healthy Pregnancy Program
- Flexible Spending & Commuter Accounts
- Pet, Home & Auto, Identity Theft and Legal Insurance