DataSMBEnterprise

Data Platform Engineer

[Company Name] is hiring a Data Platform Engineer to design and build the core infrastructure that powers our data ecosystem. You will create scalable, self-service platforms that enable data engineers, analysts, and scientists to work efficiently. This role is ideal for engineers who enjoy building internal tools and platforms that multiply the productivity of entire data teams.

Key Responsibilities

  • Design and build scalable data platform infrastructure (storage, compute, orchestration)
  • Create self-service tools and frameworks for data ingestion, transformation, and access
  • Manage and optimize data warehouse and data lake architectures
  • Implement data governance, access controls, and cataloging systems
  • Build and maintain streaming and batch data processing infrastructure
  • Collaborate with data engineering, analytics, and ML teams to understand platform needs
  • Establish best practices for data modeling, schema management, and versioning

Required Skills & Experience

  • 4+ years of experience in data engineering or platform engineering
  • Strong proficiency with Python, SQL, and at least one JVM language (Java/Scala)
  • Experience designing and managing data warehouses (Snowflake, BigQuery, or Redshift)
  • Familiarity with data lake architectures (Delta Lake, Iceberg, or Hudi)
  • Experience with distributed data processing (Spark, Flink, or Beam)
  • Understanding of Infrastructure as Code (Terraform or Pulumi)
  • Knowledge of data modeling patterns (star schema, data vault)

Nice-to-Have

  • Experience building internal developer platforms or self-service tools
  • Familiarity with data mesh or data product architectures
  • Background in real-time streaming systems (Kafka, Kinesis, Pulsar)
  • Experience with data catalogs and metadata management (DataHub, Amundsen, Atlan)
  • Knowledge of cost optimization for cloud data services

Tech Stack

PythonSparkSnowflake / BigQueryKafkaAirflowTerraformDelta Lake / IcebergKubernetesdbt

What We Offer

  • Competitive salary and equity package
  • Flexible remote or hybrid work arrangement
  • Health, dental, and vision insurance
  • Annual learning and development budget
  • Generous PTO policy

Interview Process

  1. 1Recruiter phone screen (30 min)
  2. 2Technical screen: data platform architecture and fundamentals (60 min)
  3. 3System design interview: designing a scalable data platform from scratch (60 min)
  4. 4Coding exercise: build a data ingestion pipeline or platform component (60 min)
  5. 5Hiring manager and team fit interview (45 min)