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Popular generalist data engineer role with broad required skills increases competition.
Core data engineering skills are broadly transferable across industries with low domain lock-in.
Multiple mandatory technical skills (Spark, SQL, ADF, Python) but no explicit years requirement.
Design, build, and maintain scalable data pipelines and ETL/ELT processes supporting data ingestion, transformation, storage, and reporting.
Manage data warehouses, data lakes, and data marts ensuring data quality, integrity, security, and governance.
Optimize data processing performance, troubleshoot production issues, and implement monitoring, logging, and alerting mechanisms.
Strong proficiency in SQL and experience with ETL/ELT tools and data integration frameworks.
Hands-on experience in Python, PySpark, Scala, or Java and big data technologies like Apache Spark, Hadoop, or Kafka.
Knowledge of Azure Data Factory, Azure Databricks, Azure Synapse, or equivalent cloud data platforms and relational databases (SQL Server, Oracle, PostgreSQL, or MySQL).
Bachelor's or Master’s degree in Computer Science, IT, Engineering, or related field; Work Experience Required: Not explicitly mentioned in the JD.
Experienced in developing and optimizing cloud-based data platforms with strong understanding of data warehouse concepts and dimensional modeling.
Technically proficient in big data and cloud ecosystem tools (especially Azure platform) with proven ability to manage end-to-end data pipeline lifecycle.
Operates effectively in cross-functional teams with accountability for data quality, security, and scalable data architectures.