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 using distributed data processing.
• Partner with product, analytics, and technology teams to translate business requirements into scalable data engineering solutions.
• Provide technical leadership and mentor data engineers, ensuring coding, performance, and data quality standards.
• Design and implement data frameworks to support next-generation product launches.
• Drive optimization of existing data pipelines for improved efficiency, scalability, and maintainability.

Required Skills

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

Key Skills

Education

Any Gradute