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Mid-level data engineer, remote-hybrid option, metro location, and common skillset drive high applicant competition.
Core data engineering skills and cloud tooling are highly transferable across industries.
Explicit 5+ years plus mandatory cloud, Spark, and SQL/Python skills enforce high shortlisting strictness.
Design, build, and optimize scalable ETL/ELT data pipelines processing structured and unstructured data.
Architect and maintain cloud-based data warehouses, lakes, and storage solutions ensuring high availability and performance.
Monitor, troubleshoot, and improve data pipeline performance while implementing data governance and quality frameworks.
5+ years of professional experience in data engineering, software engineering, or a similar data-focused role.
Advanced proficiency in SQL, Python, or Scala for data manipulation and pipeline development.
Hands-on experience with big data processing frameworks such as Apache Spark, Kafka, or Airflow.
Proven experience building data solutions on cloud platforms like AWS, GCP, or Azure.
Strong background in dimensional modeling, data warehousing, and data lake architectures.
Experienced in leading engineering efforts including mentoring junior engineers and conducting code reviews.
Experienced in collaborating across data scientists, product managers, and software engineers to translate requirements into reliable data models.