Data Engineer

3 weeks ago

Fort Lauderdale, Florida, United States iBusiness Funding Full time

About the Role

iBusiness Funding is a leader in providing innovative Software as a Service (SaaS) solutions for banks and lenders, with a specialization in SBA lending. We build scalable lending platforms that streamline the business lending process, allowing lenders to efficiently deliver capital to small and medium-sized businesses.

Key Responsibilities

  • Evolve our data models and architecture to support our business' demanding self-service needs
  • Develop and support ETL pipelines with robust monitoring and alarming
  • Develop data models that are optimized and aggregated for business needs
  • Develop and optimize data tables using best practices for partitioning, compression, parallelization, etc.
  • Build robust and scalable data integration (ETL) pipelines using SQL, Python, and AWS services such as Glue, Lambda, and Step Functions
  • Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
  • Interface with business customers, gathering requirements, and delivering complete reporting solutions
  • Continually improve ongoing reporting and analysis processes and automating or simplifying self-service support for customers
  • Work cross-functionally with other teams such as risk, analytics, product and more to develop data driven products and tools.

Requirements

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline
  • Experience working with large-scale data repositories like data lakes or dimensional data warehouses.
  • Ability to write high quality, maintainable, and robust code, often in SQL and Python.
  • 3+ Years of Data Warehouse Experience with Oracle, Redshift, Postgres, Snowflake etc. with demonstrated strength in SQL, Python, data modeling, ETL development, and data warehousing
  • Extensive experience working with cloud services (AWS or Azure or GCS) with a strong understanding of cloud databases (e.g. Redshift/Aurora/DynamoDB), compute engines (e.g. EMR/EC2), data streaming (e.g. Kinesis), storage (e.g. S3) etc.
  • Fundamental understanding of version control software such as Git
  • Experience with CI/CD, automated testing, and DevOps best practices
  • Candidates must be authorized to work in the U.S.

What Would Be Nice To Have

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Masters in computer science, mathematics, statistics, economics, or other quantitative fields
  • 5+ years of experience in data engineering related field in a company with large, complex data sources
  • Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
  • Experience working with AWS (Redshift, S3, EMR, Glue, Airflow, Kinesis, Step Functions)
  • Hands-on in any scripting language (BASH, C#, Java, Python, Typescript)
  • Hands on experience using ETL tools (SSIS, Alteryx, Talend)
  • Background in non-relational databases or OLAP is a plus
  • Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
  • Strong analytical skills, 5+ years' experience with Python, Scala and an interest in real time data processing
  • Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy

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