Sr. Data Engineer (AWS) - (Flexible Hybrid)

Reston, VA, United States

Fannie Mae

We facilitate equitable and sustainable access to homeownership and quality, affordable rental housing across America.

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Company Description

At Fannie Mae, futures are made. The inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to use tech to tackle housing’s biggest challenges and impact the future of the industry. You’ll be a part of an expert team thriving in an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.

Job Description


As a valued colleague on our team, you will contribute to developing data infrastructure and pipelines to capture, integrate, organize, and centralize data while testing and ensuring the data is readily accessible and in a usable state, including quality assurance.

THE IMPACT YOU WILL MAKE
The Sr. Data Engineer role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

  • Identify customer needs and intended use of requested data in the development of database requirements and support the planning and engineering of enterprise databases.
  • Maintain comprehensive knowledge of database technologies, complex coding languages, and computer system skills.
  • Support the integration of data into readily available formats while maintaining existing structures and govern their use according to business requirements.
  • Analyze new data sources and monitor the performance, scalability, and security of data.
  • Create an initial analysis and deliver the user interface (UI) to the customer to enable further analysis.

 

Qualifications

Minimum Required Experiences:

  • 2+ years of recent experience with building and deploying applications in AWS (S3, Hive, Glue, AWS Batch, Dynamo DB, Redshift, AWS EMR,  Cloudwatch, RDS, Lambda, SNS, SWS etc.)
  • 2+ years of Python, SQL, SparkSQL, PySpark
  • Excellent problem-solving skills and strong verbal & written communication skills
  • Ability to work independently as well as part of an agile team (Scrum / Kanban)

Desired Experiences:

  • Bachelor degree or equivalent
  • 4+ years experience with Big Data Hadoop clusters, AWS, and Python
  • Knowledge of Spark streaming technologies 
  • Experience in working with agile development teams
  • Familiarity with Hadoop / Spark information architecture, Data Modeling, Machine Learning (ML)
  • Knowledge of Environmental, Social, and Corporate Governance (ESG)

Skills

  • Skilled in cloud technologies and cloud computing
  • Programming including coding, debugging, and using relevant programming languages
  • Experience in the process of analyzing data to identify trends or relationships to inform conclusions about the data
  • Skilled in creating and managing databases with the use of relevant software such as MySQL, Hadoop, or MongoDB
  • Skilled in discovering patterns in large data sets with the use of relevant software such as Oracle Data Mining or Informatica
  • Experience using software and computer systems' architectural principles to integrate enterprise computer applications such as xMatters, AWS Application Integration, or WebSphere
  • Working with people with different functional expertise respectfully and cooperatively to work toward a common goal
  • Communication including communicating in writing or verbally, copywriting, planning and distributing communication, etc.

Tools

  • Skilled in AWS Analytics such as Athena, EMR, or Glue
  • Skilled in AWS Database products such as Neptune, RDS, Redshift, or Aurora
  • Skilled in SQL
  • Skilled in AWS Compute such as EC2, Lambda, Beanstalk, or ECS
  • Skilled in Amazon Web Services (AWS) offerings, development, and networking platforms
  • Skilled in AWS Management and Governance suite of products such as CloudTrail, CloudWatch, or Systems Manager
  • Skilled in Python object-oriented programming

Additional Information

The future is what you make it to be. Discover compelling opportunities at careers.fanniemae.com.

Fannie Mae is a flexible hybrid company. We embrace flexibility for our employees to work where they choose, while also providing office space for in-person work if desired. At times, business need may call for on-site collaboration, which means proximity within a reasonable commute to your designated office location is preferred unless job is noted as open to remote.

Fannie Mae is an Equal Opportunity Employer, which means we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation in the application process, email us at careers_mailbox@fanniemae.com.

The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee’s physical, mental, emotional, and financial well-being. See more here.

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Category: Engineering Jobs

Tags: Agile Architecture Athena AWS Big Data Data Mining EC2 ECS Engineering Finance Hadoop Informatica Kanban Lambda Machine Learning MongoDB MySQL OOP Oracle Pipelines PySpark Python Redshift Scrum Security Spark SQL Streaming Testing

Perks/benefits: Career development Flex hours Health care

Regions: Remote/Anywhere North America
Country: United States

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