Senior Software Engineer Data Engineering

Required skills

Master’s degree in Computer Science, Information/Systems Engineering or related field and 4 years of experience in the job offered or in a software/data engineer-related occupation. Utilize knowledge of Distributed Computing and AWS Technologies such as AWS Glue, PySpark, and AWS EMR to create highly performant pipelines that can process the data at scale. Utilize knowledge of modern Data Engineering concepts to create data lake using AWS Cloud technologies such as AWS EC2, AWS S3, AWS Lambda, AWS Spectrum, and AWS Glue. Utilize knowledge of Extract Transform and Load (ETL) to process both structured and semi-structured data. Utilize knowledge of orchestration tools such as Airflow and shell scripting for automating pipelines. Utilize knowledge of data warehousing concepts and MPP databases to create data warehouse for processing and storing large volumes of data. Utilize knowledge of Data Modeling concepts, Lucid Chart and Erwin Data Modeler to create data model for enterprise applications. Utilize knowledge of SQL for data extraction, manipulation and analysis across large datasets. Utilize knowledge of Python scripting and libraries including NumPy and Pandas to create and automate data Pipelines, for data extraction, manipulation, and data analysis. Utilize knowledge of Data Visualization tools such as AWS Quicksight and Tableau to create dashboards and generate insights. Utilize experience with working with stakeholders for providing business insights.

Preferred skills

Technologies

AWS Glue, PySpark, AWS EMR, AWS EC2, AWS S3, AWS Lambda, AWS Spectrum, Airflow, shell scripting, Lucid Chart, Erwin Data Modeler, SQL, Python, NumPy, Pandas, AWS Quicksight, Tableau.

Responsibilities

Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality. Build a scalable data platform that caters to the data plumbing needs of Chime. Build scalable data pipelines and frameworks. Architect and build workflows that could potentially become de facto standards for the fintech industry. Be a hands-on data engineer, building, scaling and optimizing ETL pipelines. Design data warehouse schemas and scale data warehouse process data for 10x data growth. Ownership of all aspects of data - data quality, data governance, data and schema design, data quality and security. Own schema registry and dependency chart for persistent data. Own the ETL workflows and make sure the pipeline meets data quality and availability requirements. Work closely with partner teams, like Data Science, Analytics and DevOps. Transform data to governed and lucid datasets. Build and deploy production-quality data pipelines. Work with stakeholders to provide business insights. Some telecommuting is permitted.

Seniority

Senior Software Engineer Data Engineering

Domain

fintech