Data Engineering Tech Lead - Hadoop Job at Cloud Analytics Technologies LLC, Cleveland, OH

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  • Cloud Analytics Technologies LLC
  • Cleveland, OH

Job Description

Key Roles & Responsibilities

  • Lead and oversee the end-to-end design, implementation, and optimization of  data pipelines supporting key customer onboarding, transaction, and decisioning workflows.
  • Architect and implement  data ingestion, transformation, and storage frameworks leveraging  Hadoop Avro , and distributed data processing technologies.
  • Partner with product, analytics, and technology teams to translate business requirements into scalable data engineering solutions that enhance real-time data accessibility and reliability.
  • Provide  technical leadership and mentorship to a team of data engineers, ensuring adherence to coding, performance, and data quality standards.
  • Design and implement robust data frameworks to support next-generation customer and business product launches.
  • Develop best practices for  data governance security , and  compliance aligned with enterprise and regulatory requirements.
  • Drive optimization of existing data pipelines and workflows for improved efficiency, scalability, and maintainability.
  • Collaborate closely with analytics and risk modeling teams to ensure data readiness for predictive insights and strategic decision-making.
  • Evaluate and integrate emerging data technologies to future-proof the data platform and enhance performance.

Must-Have Skills

  • 8–10 years of experience in  data engineering , with at least 2–3 years in a technical leadership role .
  • Strong expertise in the  Hadoop ecosystem (HDFS, Hive, MapReduce, HBase, Pig, etc.).
  • Experience working with  Avro Parquet , or other serialization formats.
  • Proven ability to design and maintain  ETL / ELT pipelines using tools such as  Spark Flink Airflow , or  NiFi .
  • Proficiency in  Python Scala for large-scale data processing.
  • Strong understanding of  data modeling data warehousing , and  data lake architectures.
  • Hands-on experience with  SQL and both  relational and  NoSQL data stores.
  • Cloud data platform experience with  AWS .
  • Deep understanding of  data security compliance , and  governance frameworks .
  • Excellent problem-solving, communication, and leadership skills.

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