Data Engineer 5 (Cloud Operations Resilience Engineering) (MEG)

Description

The team is looking for data engineers who enjoy working with emerging technologies and data, on problems that have a real business impact.

The work is a major transformation effort across the company, carried out in an Agile, collaborative, iterative setting.

Responsibilities

• Work with Agile teams to design, build, test, release and support technical solutions using full-stack tools.
• Guide developers, data analysts and data scientists who have deep experience in machine learning, distributed microservices, lakehouse architecture and full-stack systems.
• Write code in Python or Spark, work with open-source relational and NoSQL databases, and use cloud data warehouses such as Databricks and Snowflake.
• Keep up with data trends, test and learn new technologies, take part in internal and external technology communities, and coach other data practitioners.
• Partner with product managers and software engineers to deliver resilient, cloud-first data solutions that help millions of Americans reach financial empowerment.
• Design, build and ship high-quality cloud data solutions and applications on your own, with little or no day-to-day direction from supervisors or managers.
• Define and enforce shared data engineering design patterns that keep code high quality, maintainable and reusable across platforms and pipelines.
• Represent the data engineering team, explaining technical concepts and data results clearly to internal and external stakeholders so everyone shares the same understanding.
• Build data pipelines and platforms that scale, stay resilient and run efficiently as data volumes and business demand grow.
• Contribute hands-on technical work and new ideas while also mentoring peers and junior engineers to raise the whole team's skills.
• Own large, transformative data initiatives from start to finish, make key architecture decisions, and evaluate platform options such as Snowflake versus Databricks against technical and business needs.

Requirements

• Bachelor's degree or higher in Computer Science or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics or Engineering.
• At least 6 years of application development experience. Internships do not count.
• At least 4 years of distributed data experience.
• At least 4 years of SQL experience.
• At least 4 years of programming experience in Python, Java or Scala, using at least one of them.
• At least 4 years of designing and building data pipelines.
• At least 2 years of data modeling and designing end-to-end data solutions across relational and non-relational databases.
• Preferred: Master's degree in Computer Science or a related field.
• Preferred: 8+ years of data engineering experience.
• Preferred: 4+ years of data modeling experience.
• Preferred: 9+ years of application development experience, with proven skill in Python, SQL, Scala or Java.
• Preferred: 5+ years of hands-on experience designing, deploying and running data workloads on at least one public cloud (AWS, Microsoft Azure or Google Cloud).
• Preferred: 5+ years of building or supporting distributed data or compute workloads with tools such as EMR, Spark, Glue or Databricks.
• Preferred: 5+ years of designing, implementing and running real-time or streaming data pipelines.
• Preferred: 3+ years of data observability (for example Monte Carlo or Splunk) or data orchestration tools (for example Airflow or Dagster).
• Preferred: 5+ years of working with unstructured or semistructured data in NoSQL databases such as MongoDB, Cassandra or DynamoDB.
• Preferred: 5+ years of designing and supporting data warehousing solutions such as Snowflake or Redshift.
• Preferred: 3+ years of Agile development experience.
• Preferred: 3+ years of building user-centric, reusable data products.
• The company will consider sponsoring a new qualified applicant for work authorization for this role.

Conditions

Salary ranges are per full-time year and depend on location: McLean, VA $229,900 - $262,400; New York, NY $250,800 - $286,200; Plano, TX, Richmond, VA and Riverwoods, IL $209,000 - $238,500. These figures are the company's pay range at the time of posting, and the exact offer appears in the offer letter. Part-time pay is prorated to the agreed hours. Candidates hired into other locations receive that location's range.

Pay is for work performed in one of the listed locations only.

The role is eligible for performance-based incentive pay, which may include cash bonuses and or long-term incentives (LTI). Incentives may be discretionary or non-discretionary, depending on the plan.

Applications will be accepted for at least 5 business days.

Agencies should not contact the company about this role. The company is an equal opportunity employer that does not discriminate, and it considers applicants with criminal histories in line with applicable law, including New York, San Francisco, New York City and Philadelphia rules.

Accommodation requests from job seekers go to the company's recruiting team by phone or email, and information shared is kept confidential.

This posting is for the company Financial entities; roles in Canada, the United Kingdom and the Philippines are employed by the local the company entity listed for that country.

Benefits

• The company offers health, financial and other benefits that support overall well-being. Eligibility depends on full- or part-time status, exempt or non-exempt classification and management level.