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Popular generalist data role, metro hiring and medium brand create moderate candidate competition.
Core data engineering skills are transferable across industries, though GCP specialization narrows options moderately.
Multiple mandatory technical skills (GCP, Spark, Airflow, Python, SQL) increase screening rigor.
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Lead design, development, and operation of scalable data platforms using cloud services and big data technologies.
Own end-to-end data pipeline orchestration and automation, ensuring reliable integration and processing of large datasets.
Architect efficient data models and manage diverse database environments to support enterprise data needs.
Proficiency in Python and SQL; knowledge of Java or Scala is desirable.
Experience with relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, or Cassandra.
Hands-on experience with ETL/ELT tools and big data frameworks like Hadoop, Spark, and Kafka.
Experience with major cloud platforms, notably Google Cloud Platform (BigQuery, Dataflow); work experience required: Not explicitly mentioned in the JD.
Experienced in leading complex, large-scale data engineering projects within enterprise or regulated environments.
Strong background in cloud-based data architectures and workflow orchestration using tools like Apache Airflow.
Comfortable managing heterogeneous data systems and integrating multiple data sources for end-to-end data solutions.