Spark / Databricks Platform Engineer at SMART TECH SKILLS LLC | US | Rezi

Spark / Databricks Platform Engineer at SMART TECH SKILLS LLC

Spark / Databricks Platform Engineer

SMART TECH SKILLS LLC · US

2 days ago

Spark / Databricks Platform Engineer

SMART TECH SKILLS LLC · US

2 days ago
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About the Role

The Databricks Engineer designs, develops, and optimizes scalable data solutions on the Databricks platform, leveraging PySpark or Scala for large-scale data processing. This role involves constructing ingestion pipelines, implementing medallion architecture, and designing dimensional data models. The engineer collaborates with cross-functional stakeholders to gather requirements, perform cost/benefit analyses, and implement data governance, security, and quality frameworks.

Responsibilities

  • Design, develop, and optimize highly scalable data solutions on Databricks using Apache Spark, PySpark, or Scala for large-scale data processing.
  • Build, configure, and maintain robust ETL/ELT ingestion pipelines utilizing Lakeflow Declarative Pipelines.
  • Implement and maintain Delta Lake architectures and medallion database structures across Bronze, Silver, and Gold data layers.
  • Orchestrate, schedule, and monitor offline production jobs utilizing Lakeflow Jobs or equivalent tools.
  • Design, develop, and support comprehensive enterprise data warehouses utilizing dimensional data modeling, including Star and Snowflake schemas.
  • Implement rigorous data quality validation, data security controls, platform access models, and data governance frameworks.
  • Analyze system specifications, evaluate operational limitations, and perform data audits to ensure scalability, security, and cost efficiency.
  • Collaborate directly with business stakeholders, program managers, and technical peers to understand operational objectives, identify problems, and analyze current procedures.
  • Translate high-level business goals into formal technical requirements, system design documentation, and cost/benefit analyses.
  • Develop dynamic analytical dashboards and reporting solutions natively within Databricks, including Databricks SQL dashboards and Databricks Apps, to deliver actionable operational insights.

Requirements

  • 8 or more years of experience in IT, supporting the design, development, deployment, or delivery of technology solutions.
  • 8 or more years of experience with Databricks, including building and optimizing ETL/ELT data pipelines using Apache Spark.
  • 8 or more years of experience in data warehousing and dimensional data modeling, including Star and Snowflake schemas.
  • 8 or more years of professional proficiency utilizing SQL and Python (or Scala) for large-scale data processing.
  • 8 or more years of experience designing and developing dashboards and applications natively within Databricks, such as Databricks SQL dashboards or Databricks Apps.
  • 8 or more years of experience implementing data governance, data quality metrics, and data security practices.
  • 8 or more years of experience implementing Lakeflow Declarative Pipelines to build and manage production pipelines.
  • 8 or more years of experience with Delta Lake, medallion architecture, data lakehouse design, and scheduling offline jobs using Lakeflow Jobs or similar orchestration tools.
  • 8 or more years of experience communicating technical specifications and presenting data-driven insights to technical and non-technical stakeholders.
  • 1 or more years of experience working within public sector or state government environments.
  • 1 or more years of experience implementing CI/CD practices for data pipelines, including DevOps and Git-based version control workflows.

Skills

  • Apache Spark
  • PySpark
  • Scala
  • ETL/ELT
  • Lakeflow Declarative Pipelines
  • Delta Live Tables
  • Delta Lake
  • Medallion architecture
  • Bronze data layer
  • Silver data layer
  • Gold data layer
  • Lakeflow Jobs
  • Databricks Workflows
  • Apache Airflow
  • Dimensional data modeling
  • Star schema
  • Snowflake schema
  • Data quality validation
  • Data security controls
  • Platform access models
  • Data governance
  • SQL
  • Python
  • Databricks SQL dashboards
  • Databricks Apps
  • CI/CD practices
  • DevOps
  • Git-based version control
  • Analytical skills
  • Critical-thinking skills
  • Problem-solving skills
  • Communication skills

Location

  • Austin, TX

Work Type

  • Remote
  • Flexible work from home options available

Experience Level

  • Senior Level
  • 8 or more years of experience

Education Level

  • Databricks Certified Data Engineer Associate or Professional

Benefits

  • Competitive salary