Senior Data Engineer
Tampa, United States
DATAECONOMY
Enabling Businesses to Monetize Data at Data Speeds with cutting edge Technology Services and Solutions. Big Data Management, Cloud enablement, Data Science, etc..We are seeking a highly skilled and experienced Senior Data Engineer to lead the end-to-end development of complex models for compliance and supervision. The ideal candidate will have deep expertise in cloud-based infrastructure, ETL pipeline development, and financial domains, with a strong focus on creating robust, scalable, and efficient solutions.
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Key Responsibilities:
βββββββ’βββββModel Development: Lead the development of advanced models using AWS services such as EMR, Glue, and Glue Notebooks.
βββββββ’βββββCloud Infrastructure: Design, build, and optimize scalable cloud infrastructure solutions with a minimum of 5 years of experience.
βββββββ’βββββETL Pipeline Development: Create, manage, and optimize ETL pipelines using PySpark for large-scale data processing.
βββββββ’βββββCI/CD Implementation: Build and maintain CI/CD pipelines for deploying and maintaining cloud-based applications.
βββββββ’βββββData Analysis: Perform detailed data analysis and deliver actionable insights to stakeholders.
βββββββ’βββββCollaboration: Work closely with cross-functional teams to understand requirements, present solutions, and ensure alignment with business goals.
βββββββ’βββββAgile Methodology: Operate effectively in agile or hybrid agile environments, delivering high-quality results within tight deadlines.
βββββββ’βββββFramework Development: Enhance and expand existing frameworks and capabilities to support evolving business needs.
βββββββ’βββββDocumentation and Communication: Create clear documentation and present technical solutions to both technical and non-technical audiences.
Requirements
β’βββββ10+ years of experience with Python programming.
βββββββ’βββββ5+ years of experience in cloud infrastructure, particularly AWS.
βββββββ’βββββ3+ years of experience with PySpark, including usage with EMR or Glue Notebooks.
βββββββ’βββββ3+ years of experience with Apache Airflow for workflow orchestration.
βββββββ’βββββSolid experience with data analysis in fast-paced environments.
βββββββ’βββββDomain Expertise:
βββββββ’βββββStrong understanding of capital markets, financial systems, or prior experience in the financial domain is a must.
βββββββ’βββββTechnical Skills:
βββββββ’βββββProficiency with cloud-native technologies and frameworks.
βββββββ’βββββFamiliarity with CI/CD practices and tools like Jenkins, GitLab CI/CD, or AWS CodePipeline.
βββββββ’βββββExperience with notebooks (e.g., Jupyter, Glue Notebooks) for interactive development.
βββββββ’βββββExcellent problem-solving skills and ability to handle complex technical challenges.
βββββββ’βββββStrong communication and interpersonal skills for collaboration across teams and presenting solutions to diverse audiences.
βββββββ’βββββAbility to thrive in a fast-paced, dynamic environment.
Preferred Qualifications:
βββββββ’βββββExperience with data governance and compliance frameworks.
βββββββ’βββββFamiliarity with machine learning frameworks and techniques for financial modeling.
βββββββ’βββββCertifications in AWS or other cloud technologies.
Benefits
βββββββ’βββββCompetitive compensation and benefits.
βββββββ’βββββOpportunity to work on cutting-edge compliance and supervision technologies.
βββββββ’βββββCollaborative and innovative work environment.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index π°
Tags: Agile Airflow AWS CI/CD Data analysis Data governance ETL GitLab Jenkins Jupyter Machine Learning ML models Pipelines PySpark Python
Perks/benefits: Career development Competitive pay
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