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Antino - Senior Data Engineer - Databricks/Azure

Antino - Senior Data Engineer - Databricks/Azure

Antino Labs
Early Applicant
  • Posted 14 hours ago
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Job Description

Role Overview

We are seeking a Senior Data Engineer to drive cloud data modernization and build scalable, AI-ready data platforms. This role emphasizes expertise in Databricks, PySpark, Azure Data Factory, Logic Apps, and Airflow, with a strong focus on orchestration, pipeline reliability, and end-to-end data workflow management.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines using Databricks (PySpark), ADF, Logic Apps, and Airflow
  • Develop and manage end-to-end orchestration frameworks integrating Airflow DAGs with ADF and Logic Apps
  • Implement advanced workflow orchestration patterns (event-driven, micro-batch, hybrid scheduling)
  • Ensure pipeline dependency management, execution reliability, and operational excellence
  • Build high-performance ETL/ELT pipelines using Databricks and Delta Lake architecture
  • Implement data observability, monitoring, and alerting mechanisms across workflows
  • Optimize pipelines and workflows for performance, scalability, and cost efficiency
  • Integrate pipelines with Azure services such as ADLS Gen2, Blob Storage, and event triggers
  • Implement CI/CD for pipelines and workflows using GitHub Actions or equivalent
  • Ensure data quality, governance, and security compliance
  • Collaborate with data science teams for ML/GenAI data readiness
  • Mentor junior engineers and drive best practices for orchestration and pipeline design.

Required Qualifications

  • 7+ years of experience in data engineering
  • Highly proficient in Databricks (PySpark, Delta Lake), Azure Data Factory (ADF), Azure Logic Apps, and Apache Airflow
  • Exposure to AI/ML and Llm data pipelines and MLflow
  • Strong programming skills in Python and advanced SQL
  • Experience in building orchestrated data platforms with multi-tool integration
  • Strong understanding of ETL/ELT patterns and orchestration frameworks
  • Experience in cloud-native data architectures (Azure preferred)
  • Hands-on experience with monitoring, logging, and pipeline reliability

(ref:hirist.tech)

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