Data Engineer with Databricks

Artech LLC
  • Tampa, FL
  • $44–$47 Per Hour
  • Instant Apply
30+ days ago

Job Description

Request ID: 107834-1
Title: Data Engineer with Databricks
Locations: Tampa, FL
Duration: 6 Months
Pay Range: $44 - $47/Hour on W2/C2C (All inclusive)

We are seeking an experienced Data Engineer with 4 6 years of experience and strong hands-on expertise in Databricks and Apache Spark. The ideal candidate will design, develop, and optimize scalable data pipelines to support analytics and data-driven business initiatives.

The candidate will work closely with data scientists, analysts, business stakeholders, and cross-functional teams to ensure data is reliable, secure, high-quality, and readily available.

Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and Apache Spark.
  • Build and optimize batch and real-time/streaming data pipelines for large volumes of structured and unstructured data.
  • Develop data engineering solutions using Databricks, Spark, and related data technologies.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.
  • Monitor, troubleshoot, and optimize data processing workflows to ensure reliability and performance.
  • Optimize Databricks clusters for performance, scalability, and cost efficiency.
  • Implement data quality, governance, security, and compliance standards across data pipelines.
  • Perform data validation and troubleshooting to identify and resolve pipeline issues.
  • Maintain technical documentation related to data architecture, data pipelines, workflows, and processes.
  • Support continuous improvement of data engineering processes and platform capabilities.
  • Explore and integrate AI/Agentic AI capabilities into data engineering workflows where applicable.

Required Skills

  • 4 6 years of experience in Data Engineering.
  • Strong hands-on experience with Databricks.
  • Strong experience with Apache Spark.
  • Experience developing ETL/ELT pipelines.
  • Experience with both batch and streaming data processing.
  • Experience working with large volumes of structured and unstructured data.
  • Strong understanding of data engineering and data processing concepts.
  • Experience with data pipeline monitoring, troubleshooting, and performance optimization.
  • Knowledge of data governance, security, and compliance.
  • Experience optimizing Databricks clusters for cost and performance.
  • Strong problem-solving and analytical skills.
  • Good communication and collaboration skills.

Preferred Skills

  • Experience with AI Agents / Agentic AI.
  • Experience integrating AI capabilities into data platforms or data workflows.
  • Knowledge of cloud data platforms such as AWS, Azure, or GCP.
  • Experience with streaming technologies such as Kafka.
  • Knowledge of data lake/lakehouse architecture.

Numbers & Facts

LocationTampa, FL
Salary$44–$47 Per Hour

Skills

  • Amazon Web Services (AWS)unmatched
  • Analysis Skillsunmatched
  • Apache Sparkunmatched
  • Artificial Intelligence (AI)unmatched
  • Artificial Intelligence (AI) Agentsunmatched
  • Cloud Computingunmatched
  • Communication Skillsunmatched
  • Continuous Improvementunmatched
  • Cross-Functionalunmatched
  • Data Analysisunmatched
  • Data Lakeunmatched
  • Data Managementunmatched
  • Data Processingunmatched
  • Data Qualityunmatched
  • Data Scienceunmatched
  • Database Extract Transform and Load (ETL)unmatched
  • GCP (Good Clinical Practices)unmatched
  • Identify Issuesunmatched
  • Information/Data Security (InfoSec)unmatched
  • Microsoft Windows Azureunmatched
  • Performance Tuning/Optimizationunmatched
  • Problem Solving Skillsunmatched
  • Process Capabilityunmatched
  • Process Improvementunmatched
  • Regulatory Complianceunmatched
  • Scalable System Developmentunmatched
  • Streaming Technologyunmatched
  • Structured Dataunmatched
  • Team Playerunmatched
  • Technical Writingunmatched
  • Unstructured Dataunmatched

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