About the position
The Marketing Analytics and Technology team is an enabling function supporting the Business Unit Marketing and Enterprise Analytics & Customer Experience teams (EACX) and thereby the Chief Product Officers/Line of Business, responsible for measuring, assessing and articulating the efficacy of our marketing strategies to help drive growth and/or efficiency opportunities across the bank. With sister teams participating alongside the marketing lifecycle of the various segments, the Marketing Analytics Product Owner team is enabling those analysts with the data, tools, frameworks and centralized reporting they need to generate insights and report on performance. In addition, this team supports horizontal program/channel level insights and centralized experimentation strategy and governance. As a Data Engineer on the Marketing Analytics Product Owner team, you'll play a key role in the growth and long-term success of the marketing data product. Joining a team of Data & Analytics Engineers, you'll work closely with Marketing Analytics leadership, our Data Product and Platform team, and marketing analysts to deliver innovative data solutions that align to our data product strategy. We are a forward-thinking organization currently operating a robust on-premise data analytics platform and planning an exciting migration to Azure within the next year. Our goal is to modernize our data stack while maintaining seamless operations during this transformative period. As a Data Engineer, you will play a critical role in ensuring our current infrastructure remains efficient and reliable while contributing to the design and implementation of our cloud-based data solutions.
Responsibilities
- Maintain and optimize the existing on-premise data platform, which includes technologies like Hadoop, Presto, Greenplum, and Airflow.
- Monitor and enhance ETL pipelines to ensure timely, accurate, and efficient data processing.
- Troubleshoot and resolve data pipeline and infrastructure issues to minimize downtime.
- Collaborate with data analysts, data scientists, and business stakeholders to meet their data needs.
- Partner with cross-functional teams to design the architecture for our migration to Azure (and possibly AWS).
- Develop proof-of-concept solutions to validate migration strategies and tools.
- Ensure the secure and efficient transfer of data assets from on-premise to cloud environments.
- Identify and address potential risks and challenges during the migration process.
- Refactor and modernize ETL/ELT pipelines using dbt and SQL to optimize data transformation and processing workflows.
- Integrate open-source tools like DuckDB and Polars to support data transformation and analysis.
- Build scalable, reusable, and automated data pipelines compatible with multi-cloud environments.
- Implement data quality checks and monitoring using tools such as Great Expectations.
- Ensure compliance with data governance policies and standards.
- Enable data lineage tracking to enhance transparency and reliability.
- Contribute to version-controlled, shared codebases in Git repositories.
- Write and maintain detailed documentation for workflows, pipelines, and processes.
- Provide knowledge transfer and training sessions to empower team members and stakeholders.
Requirements
- Bachelor's degree in a related field, or equivalent work experience.
- Five to seven years of statistical and/or data analytics experience.
Nice-to-haves
- 5+ years of experience in data engineering, including hands-on experience with on-premise data platforms.
- Proficiency in SQL, Python, and data pipeline tools like Airflow or similar.
- Experience with cloud platforms, preferably Azure or AWS.
- Familiarity with modern data stack tools such as dbt, Docker, and Git.
- Strong problem-solving and troubleshooting skills.
- Excellent communication and collaboration abilities.
- Experience with Hadoop, Presto, or Greenplum.
- Knowledge of data transformation frameworks like Polars.
- Familiarity with data visualization tools such as Power BI or Tableau.
- Understanding of data governance and security best practices.
- Exposure to agile project management methodologies.
Benefits
- Healthcare (medical, dental, vision)
- Basic term and optional term life insurance
- Short-term and long-term disability
- Pregnancy disability and parental leave
- 401(k) and employer-funded retirement plan
- Paid vacation (from two to five weeks depending on salary grade and tenure)
- Up to 11 paid holiday opportunities
- Adoption assistance
- Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law
