Data Engineer - ETL/Python - Banking

Job Requirements

• High School Diploma, GED, or foreign equivalent required.
• Bachelor's in Computer Science, Mathematics or related field + 10 years of development experience preferred, or 10 years comparable work experience required.
• 10 years of experience designing, developing, testing, and implementing Extract, Transform and Load (ELT/ETL) solutions using enterprise ELT/ETL
• 15 years of comparable work experience.
• 10 years of experience developing and implementing data integration, data lake and data warehouse solutions in an on-premise and cloud environment.
• 5 years of experience working with Business Intelligence tools (IBM Cognos is preferred), Power BI and Alteryx.
• 7 years of experience working with API's, data as a service, data marketplace and data mesh.

Skills & Experience

• 10 years of experience with various Software Development Life Cycle methods such as Agile, SCRUM, Waterfall, etc.
• 3-year experience in 100+ TB data environment.
• Proven experience developing and maintaining data pipelines and ETL jobs using IBM DataStage, Informatica, Matillion, FiveTran, Talend or Dbt
• Knowledge of AWS cloud services such as S3, EMR, Lambda, Glue, Sage Maker, Redshift & Athena and/or Snowflake.
• Experienced in data modelling for self-service business intelligence, advanced analytics, and user application.
• Experience with Data Science including AI/ML Engineering, ML framework/pipeline build and predictive/prescriptive analytics on Aws Sagemaker.

Responsibilities

The Sr. Data Engineer is responsible in understanding and supporting the businesses through the design, development, and execution of Extract, Transform, and Load (ELT/ETL), data integration, and data analytics processes across the enterprise. He/She will stay on top of tech trends, experiment with and learn new technologies, contribute to the growth of data organization, participate in internal & external technology communities, and mentor other members of the team.

Job Responsibilities

• Technical Leadership
  • Lead data integration across the enterprise thru design, build and implementation of large scale, high volume, high performance data pipelines for both on-prem and cloud data lake and data warehouses.
  • Lead the development and documentation of technical best practices for ELT/ETL activities.
• Solution Design
  • Lead the design of technical solution including code, scripts, data pipelines, processes/procedures for integration of data lake and data warehouse solutions in an operative IT environment.
• Code Development
  • Ensures data engineering activities are aligned with scope, schedule, priority and business objectives.
  • Oversees code development, unit and performance testing activities.
• Testing
  • Leads validation efforts by verifying the data at various middle stages that are being used between source and destination and assisting others in validating the solution performs as expected.
  • Meets or exceeds all operational readiness requirements (e.g., operations engineering, performance, and risk management).