Data Engineer - FinTech, Fintech

Overview

We are seeking a highly skilled Data Engineer to join our Fin Tech ADA team, responsible for building and optimizing scalable data pipelines and platforms that power analytics, automation, and decision-making across Finance and Accounting domains. The ideal candidate will have strong expertise in AWS cloud technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM, along with hands‑on experience designing secure, efficient, and resilient data architectures.

• Work with large‑scale structured and unstructured datasets, leveraging both relational and non‑relational data stores to deliver reliable, high‑performance data solutions.
• Translate business needs into technical data solutions, collaborating with cross‑functional teams.
• Build scalable data pipelines, optimize existing pipelines, and maintain operation excellence for the Accounting and Data Analytics team.
• Focus on building and maintaining data platforms for sourcing, merging, and transforming financial datasets to extract business insights, improve controllership, and support financial month‑end close periods.

• 5+ years experience as a Data Engineer or in a similar role.
• Experience with data modeling, data warehousing, and building ETL pipelines.
• Extensive experience working with AWS, including Redshift, EMR, Athena, Aurora, Dynamo
  
  DB, Kinesis, Lambda, S3, EC2, etc.
• Proficiency in coding languages such as Python, Java, or Scala.
• Experience maintaining data warehouse systems and working on large‑scale data transformation using EMR, Hadoop, Hive, or other Big Data technologies.
• Experience mentoring and managing other Data Engineers, ensuring data engineering best practices are being followed.
• Experience with hardware provisioning, forecasting hardware usage, and managing a budget.
• Exposure to large databases, BI applications, data quality, and performance tuning.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with SQL.

• 5+ years of data engineering experience.
• Experience with non‑relational databases and data stores (object storage, document or key‑value stores, graph databases, column‑family databases).

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