Overview

We are a values driven organization putting Relationships FIRST. EagleBank (NASDAQ – EGBN) is focused on being Flexible, Involved, Responsive, Strong, and Trusted. By prioritizing meaningful connections with our customers, employees, and shareholders, we relentlessly deliver the most compelling, valuable service to our customers.

EagleBank is committed to inclusion, equity, and respect. We celebrate diversity and intentionally seek out opportunities to learn from one another’s experience. We believe employees are essential to the building of relationships and we prioritize investing in employee growth and wellbeing. Employee involvement is fostered through resource groups, mentorship programs, community service, and scholarship opportunities for continued education. With features including maternity and parental leaves, wellness discounts, healthcare premium sharing, employer funding in your HSA account, and 100% 401(k) matching up to 4%, we pride ourselves in the ways we support our internal relationships.

We understand the need to be creative and flexible when it comes to telecommuting and other alternative work arrangements. This position is eligible for our hybrid remote work and will work in the Bethesda, MD office four days per week.

Responsibilities

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Eagle Bank, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs. We are seeking a Data Engineer who is passionate about marrying data with emerging technologies. As Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Eagle Bank. We are a place where we take pride in our low egos, value curiosity and learning.

Qualifications

Duties & Responsibilities:

• Build and optimize data pipelines for efficient data ingestion, transformation, and loading from various sources while ensuring data quality and integrity.
• Support the design and development of scalable data architectures and systems that extract, store, and process large amounts of data.
• Collaborate with Business Analysts and/or Product Owners, internal customers to understand their requirements and provide efficient solutions for data exploration, analysis, and modeling.
• Implement testing, validation and pipeline observability to ensure data pipelines are meeting customer SLAs.
• Use cutting edge technologies such as Python, Scala, Spark, and a variety of Cloud services to develop modern data pipelines supporting Machine Learning and Artificial Intelligence.

Requirements:

• Bachelor’s Degree with at least 4 years of experience working with relational databases (e.g., MySQL); advanced SQL skills are required for this role.
• 4 years of experience building and designing ETL data pipelines using Python, Java, or Scala.
• 3 years of experience with a public cloud (e.g., Microsoft Azure, AWS, Google Cloud).
• 3 years of experience using Spark or PySpark.
• 3 years of data warehousing experience (MS Synapse or Redshift or Snowflake).
• 2 years of experience optimizing data schemas, validating data integrity and data quality (DIDQ), data governance, lineage.

Preferences:

• Experience with big data technologies such as Hadoop and Spark to efficiently process and analyze massive datasets.
• Experience handling data sets related to financial services (e.g., loans).
• Experience / familiarity with basics of data science and predictive modelling.
• 2 years of experience with Agile engineering practices.

Don't meet all the requirements? We encourage you to still apply if you think you are the right person to join our community. We are always interested connecting with people inspired by our mission and values. If you aren’t hired for this position, your resume will remain available for the next year and might be considered for future openings. Note: You can update your resume as often as needed.