Data Engineer
4 weeks ago
iBusiness Funding is a leader in providing innovative Software as a Service (SaaS) solutions for banks and lenders, with a specialization in SBA lending. Our team is driven by our core values of innovation, integrity, enjoyment, and family.
We're seeking a skilled Data Engineer to scale our existing infrastructure, incorporate new data sources, and build robust data pipelines. As a key player in our data-driven initiatives, you will work backwards from our business questions to drive scalable solutions.
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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