Description

You will lead the end-to-end design, implementation, and optimization of data pipelines supporting customer onboarding, transaction, and decisioning workflows.

Responsibilities

• Architect and implement data ingestion, transformation, and storage frameworks leveraging Hadoop and distributed data processing.
• Translate business requirements into scalable data engineering solutions, partnering with product and analytics teams.
• Provide technical leadership and mentor data engineers, enforcing coding, performance, and data quality standards.
• Design and implement data frameworks to support new customer and business product launches.
• Drive pipeline optimization and develop best practices for data governance and security.

Required Skills

• 8+ years of experience in data engineering, including 2-3 years in a technical leadership capacity.
• Strong expertise in the Hadoop ecosystem (HDFS, Hive, MapReduce, HBase, Pig, etc.).
• Proficiency in Python and Scala for large-scale data processing.
• Proven ability to design and maintain ETL/ELT pipelines using Spark, Flink, Airflow, or NiFi.
• Experience working with Avro and Parquet serialization formats.
• 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, specifically with AWS.
• Deep understanding of data security, compliance, and governance frameworks.

Key Skills

Education

Any Graduate