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IT services & solutions and digital transformation

Azure Data Engineer

Posted: 2 months ago
Job Location
Remote Work Policy

In office

Visa Sponsorship

Not Available

RelocationAllowed
Skills
Python
SQL
Spark SQL
Pyspark
CI/CD
Azure Databricks
Delta Lake
Delta Live Tables
Databricks Workflows

About the job

Required Qualifications & Experience

  • Bachelor's degree in computer science, Information Technology, Engineering, or a related discipline, with 6-10 years of experience in Data Engineering, Application Development, System Integration, or Enterprise Data Warehouse projects.
  • Strong hands-on experience designing and implementing modern data platforms on Azure Databricks, leveraging Delta Lake, Delta Live Tables (DLT), and Medallion Architecture (Bronze, Silver, Gold) to build scalable and reliable data pipelines.
  • Proven expertise in developing and optimizing batch and streaming data pipelines using PySpark, Spark SQL, and Python, with a strong focus on performance tuning, scalability, and cost optimization.
  • Extensive experience in Databricks job performance optimization, including query tuning, partitioning strategies, data skew mitigation, caching, cluster sizing, workload optimization, and Spark execution plan analysis.
  • Strong proficiency in SQL programming and data modeling concepts, including relational, dimensional, and lakehouse data architectures.
  • Deep understanding of Delta Lake features such as ACID transactions, schema evolution, time travel, change data capture (CDC), and data quality enforcement.
  • Experience implementing data quality, monitoring, and orchestration frameworks using Delta Live Tables expectations, Databricks Workflows, and Azure-native services.
  • Strong exposure to the full Software Development Life Cycle (SDLC), including design, development, testing, CI/CD, deployment, and production support.
  • Solid understanding of Lakehouse architecture, cloud-based analytics platforms, data governance, and data engineering best practices.
  • Knowledge of real-time data processing, data integration patterns, and enterprise-scale data migration initiatives is a strong advantage.
  • Demonstrated ability to stay current with evolving cloud and big data technologies and contribute effectively to architecture discussions, technology strategy, and platform modernization initiatives.
  • Self-motivated, proactive, and capable of working independently in a fast-paced environment while collaborating with globally distributed teams.
  • Strong analytical, problem-solving, communication, and stakeholder management skills.

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