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Job Description
Structured overview of role & requirementsAbout This Role
Own the design, implementation, and operation of scalable, resilient data engineering solutions using cloud-based infrastructure and Agile methods.
Collaborate cross-functionally with Data Engineers, Analysts, Scientists, DBAs, and business partners to transform disparate data into actionable insights for decision-making.
Lead technical projects, ensuring high-quality data pipelines, test coverage, and adoption of new technologies to improve data reliability and efficiency.
Minimum Requirements
Bachelor of Science degree in Computer Science or equivalent.
Minimum 7 years post-degree professional experience with at least 4 years in ETL pipeline development and 3 years Python development experience.
Hands-on experience with AWS integrations including Kinesis, Firehose, Redshift, Aurora Unload, EMR, SageMaker, and Lambda.
Strong SQL skills including performance tuning and NoSQL database design; familiarity with data orchestration tools such as Argo or Airflow.
Ideal Candidate Profile
Experienced in managing end-to-end data lifecycle and developing data solutions that support machine learning, analytics, and reporting.
Capable of leading and mentoring junior engineers, with experience driving adherence to coding best practices through code reviews.
Operates effectively in a fast-paced Agile environment, collaborating with diverse technical and business teams in a financial services context.