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Senior Data Engineer

Enable Data Incorporated

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Original Job Summary

Senior Data Engineer

Enable Data Incorporated is seeking a Senior Data Engineer to design, develop, and maintain scalable data solutions in the cloud using Apache Spark and Databricks.

Responsibilities include:

  • Design, develop, and maintain cloud-based data solutions.
  • Gather and analyze data requirements and identify insights.
  • Build and optimize data pipelines using Spark and Databricks.
  • Ensure data quality, integrity, and security across data lifecycle.
  • Collaborate with cross-functional teams on data models and storage solutions.
  • Tune Spark jobs and leverage Databricks features for optimization.
  • Provide guidance and expertise to junior team members.
  • Stay updated on emerging trends in cloud computing and big data.
  • Contribute to the improvement of data engineering processes and best practices.

Required Experience and Skills:

  • 10+ years in Data or Software Engineering with cloud solution focus.
  • Expertise in Azure cloud, Databricks, EventHub, Kafka, Spark, and ETL pipelines.
  • Proficiency in Python, PySpark, and SQL.
  • Experience with large-scale distributed systems and architecture design.
  • Bachelor’s or Master’s in Computer Science, Engineering, or related field.

Mode of Work: Remote

Notice Period: Immediate joiners preferred; join by September 15th, 2025.

Key skills/competency

  • Azure
  • Databricks
  • Spark
  • Kafka
  • EventHub
  • Python
  • SQL
  • ETL
  • Architecture
  • Cloud

How to Get Hired at Enable Data Incorporated

🎯 Tips for Getting Hired

  • Research Enable Data Incorporated's culture: Study their mission and recent developments on LinkedIn.
  • Customize your resume: Highlight cloud and big data projects.
  • Emphasize technical skills: Showcase Azure, Databricks, and Spark expertise.
  • Prepare for interviews: Review architecture and pipeline optimization scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review Azure cloud fundamentals.
Practice Spark job optimization techniques.
Study Databricks and pipeline frameworks.
Brush up on Python and SQL coding.

Behavioral Questions

Describe a complex project collaboration.
Explain decision-making under pressure.
Share conflict resolution experiences.
Discuss adaptability to new technologies.