a highly skilled and experienced Data Engineer to join our growing Data Operations team. The ideal candidate will have a strong background in data modeling, database design principles, ETL development using SQL and Python, and modern data engineering practices in Snowflake. In this role, you will play a key part in designing, building, validating, deploying, and maintaining scalable data pipelines, governed data workflows, and reliable data infrastructure to support analytics, reporting, business intelligence, and stakeholder data needs. We’re looking for someone who thrives in a collaborative Agile environment, follows DevOps and source control best practices, is eager to learn, and enjoys solving complex data challenges. Your work will positively impact millions of account holders across hundreds of financial institutions.
Key Responsibilities:
- Design, develop, validate, deploy, and maintain robust ETL pipelines and governed data workflows using SQL and Python
- Build scalable data models, curated datasets, and reusable data structures that support analytics, reporting, dashboards, and stakeholder data needs
- Implement and optimize data storage and processing solutions using MS SQL Server and Snowflake
- Design and maintain Snowflake pipelines using a standard medallion architecture, including raw, refined, and curated data layers
- Create dynamic tables and derived tables to transform raw data sources into appropriate presentation-layer outputs
- Implement data validation, quality checks, reconciliation processes, and issue resolution to ensure accurate, complete, and reliable data outputs
- Collaborate with data analysts, data scientists, developers, and business stakeholders in an Agile Scrum environment to translate requirements into data solutions
- Supply prepared data to visualization tools, client-facing dashboards, reporting outputs, and secure third-party data deliveries
- Use Azure DevOps or similar tools to manage CI/CD pipelines, deployments, work items, source control, code reviews, and release processes
- Handle file ingestion, parsing, and ongoing maintenance of existing data pipelines and applications
- Develop and maintain documentation for data processes, architecture, governance, and operational standards
Required Qualifications:
- Bachelor’s degree in Computer Science, IT, a related field, or equivalent experience
- 5+ years of professional experience as a Data Engineer or in a similar role
- Experience designing, building, maintaining, and troubleshooting ETL pipelines and data workflows
- Strong proficiency in SQL and Python, including complex SQL queries, stored procedures, scripting, and analysis using tools such as Jupyter Notebooks
- Strong understanding of data warehouse concepts, relational datasets, SQL joins, database design principles, and fact and dimensional table design
- Experience designing and maintaining dimensional models, curated datasets, and reusable data structures for analytics and reporting
- Hands-on experience with MS SQL Server and Snowflake, including Snowflake medallion architecture for raw, refined, and curated data layers
- Ability to implement data validation, quality checks, reconciliation processes, issue resolution, and governance practices to ensure trusted data outputs
- Experience with data orchestration tools such as Azure Data Factory, dbt, or Apache Airflow
- Experience using Azure DevOps or similar DevOps tools to support CI/CD pipelines, deployment automation, work item tracking, source control, branching strategies, pull requests, code reviews, coding standards, and release management
- Familiarity with Looker or similar BI tools
- Experience with containerization technologies such as Docker or OCI
- Knowledge and experience with SSRS/SSIS reports and report server administration
- Knowledge and experience with PowerShell, including the ability to read and write scripts
- Strong problem-solving, debugging, communication, collaboration, and influencing skills across meetings, email, and ticketing systems
- Team-player mentality with the ability to work effectively in a collaborative technical environment
Preferred Qualifications:
- Background working with financial data and knowledge of banking or credit institutions and their transactions
- Experience with cloud data platforms and services
- Familiarity with Postgres and Oracle PL/SQL
- Familiarity with C#
- Ability to read and write R scripts to compile datasets
