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Senior Data Engineer (Databricks & Big Data)

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AI Summary

Lead the design, development, and optimization of scalable data pipelines and lakehouse architectures using Databricks, Apache Spark, and cloud platforms. Drive automation, CI/CD, and performance tuning while ensuring data governance and integration across hybrid environments. Collaborate with cross-functional teams to deliver robust ETL/ELT solutions and enhance data-driven decision-making.

Key Highlights
8+ years of hands-on experience in Data Engineering and Big Data with a focus on Databricks and Apache Spark
Responsibility for end-to-end data pipeline development, performance tuning, and cloud infrastructure automation
Leadership in implementing secure, scalable, and efficient data lakehouse architectures across hybrid environments
Key Responsibilities
Design, build, and optimize scalable data pipelines using Databricks, Apache Spark, and PySpark
Develop and maintain CI/CD pipelines, automation workflows, and infrastructure-as-code solutions (e.g., Terraform)
Ensure data lakehouse architecture best practices, including Delta Lake, data governance, and security compliance
Technical Skills Required
Databricks Apache Spark Python
Benefits & Perks
Visa sponsorship available
Hybrid work arrangement (Atlanta, GA)
Nice to Have
Azure Data Factory (ADF) or similar orchestration tools
Kafka or other streaming technologies
Unity Catalog and Databricks security/governance expertise

Job Description


HYBRID - Atlanta GA


Only W2 - No Corp to Corp


Open to Sponsorship



Required Skills & Experience

  • 8+ years of experience in Data Engineering / Big Data.
  • 5+ years of hands-on experience with Databricks.
  • Strong experience with Apache Spark / PySpark.
  • Strong programming skills in Python and SQL.
  • Extensive experience with Delta Lake and Databricks Workflows/Jobs.
  • Strong understanding of data lake and lakehouse architectures.
  • Hands-on experience with Azure, AWS, or GCP.
  • Strong DevOps experience with CI/CD pipelines and automation.
  • Experience with Azure DevOps, GitHub, GitLab, or Jenkins.
  • Experience with Terraform or Infrastructure as Code.
  • Strong experience with Git and source-code management.
  • Experience deploying Databricks solutions across multiple environments.
  • Strong understanding of ETL/ELT concepts and data integration.
  • Experience with performance tuning and optimization of Spark/Databricks workloads.

Preferred Skills

  • Experience with Azure Data Factory (ADF) or similar orchestration tools.
  • Experience with Kafka or other streaming technologies.
  • Experience with Unity Catalog and Databricks security/governance.
  • Experience with REST APIs and Databricks APIs.
  • Knowledge of Docker and Kubernetes.
  • Experience with automated testing and code-quality tools.
  • Databricks or cloud certifications are a plus.



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