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Data Engineering Tech Lead – Hadoop

Quantum Technologies LLC

 

Cleveland, OH, USA

Posted On: 4 days ago
Experience: 8+ years
Availability: Onsite
Openings: 1
Category: Data Engineering Lead
Tenure: No Preference/Any
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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.


 

Education

Any Graduate

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