About the role

  • Senior Data Engineer designing and developing scalable data pipelines for fintech company. Collaborating with stakeholders to ensure analytics-ready data formats and supporting batch and streaming processes.

Responsibilities

  • Design, develop, and maintain scalable data pipelines using Apache Spark (PySpark and/or Scala)
  • Build and optimize data workflows on Databricks , including Delta Lake, notebooks, and scheduled jobs
  • Ingest, transform, and curate large-scale structured and semi-structured datasets
  • Perform performance tuning and cost optimization of Spark workloads and Databricks clusters
  • Implement data quality checks, monitoring, and error handling
  • Collaborate with analytics and business stakeholders to deliver well-modeled, analytics-ready data
  • Support batch processing and, where applicable, streaming data pipelines
  • Follow best practices for testing, documentation, security, and version control

Requirements

  • 5+ years of experience in Data Engineering or related roles
  • Strong hands-on experience with Apache Spark (PySpark or Scala)
  • Proven experience working in Databricks environments
  • Strong SQL skills and experience with relational and analytical databases
  • Experience building and maintaining ETL/ELT pipelines at scale
  • Familiarity with modern data lake architectures (Delta Lake preferred)
  • Experience with Git-based version control

Benefits

  • Flexible work from home options

Job title

Senior Data Engineer

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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