Description

You will lead the design, implementation, and optimization of data pipelines for customer onboarding, transaction, and decisioning workflows.

This role is on-site.

Responsibilities

• Architect and implement data ingestion, transformation, and storage frameworks using distributed data processing.
• Partner with product and analytics teams to translate requirements into scalable data engineering solutions.
• Provide technical leadership and mentorship to data engineers, enforcing coding and quality standards.
• Design and implement data frameworks to support new customer and business product launches.
• Drive optimization of existing data pipelines for efficiency, scalability, and maintainability.

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).
• Proven ability to design and maintain ETL/ELT pipelines using Spark, Flink, Airflow, or NiFi.
• Proficiency in Python and Scala for large-scale data processing.
• Hands-on experience with SQL and both relational and NoSQL data stores.
• Cloud data platform experience with AWS.
• Experience with Avro, Parquet, or other serialization formats.
• Deep understanding of data modeling, data warehousing, and data lake architectures.

Key Skills

Education

Any Graduate