Data Engineer 5

Description

The team manages data technology, platforms and experiences across the company, with the goal of making data easy to find, use, understand, govern and protect across the full data lifecycle.

The platforms cover the data pipeline, including storage and access. Going forward, the work centres on expanding the company's AI capabilities and growing its data platforms.

This is a senior data engineering role for someone who enjoys combining data work with new technologies and will help drive a major transformation across the company.

The role suits people who like solving complex business problems in an agile, collaborative and iterative setting.

Responsibilities

• Work with agile teams to design, build, test, release and support technical solutions using full-stack tools.
• Guide a group of 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 mentor members of the data community.
• Partner with product managers and software engineers to deliver reliable cloud-first data solutions that help millions of Americans reach financial empowerment.
• Design, build and deliver high-quality cloud data solutions and applications 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, easy to maintain and reusable across platforms and pipelines.
• Act as the data engineering team's spokesperson, explaining technical concepts and data results clearly to internal and external stakeholders.
• Design and build data pipelines and platforms that scale, recover from failure and run efficiently as data volumes and business demands grow.
• Combine hands-on technical work and new ideas with mentoring, raising the skills of peers and junior engineers.
• Lead large, transformative data initiatives from start to finish, making key architecture decisions and assessing platform options such as Snowflake versus Databricks against technical and business needs.

Requirements

• A 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. Internship time does 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.
• At least 4 years of designing and developing data pipelines.
• At least 2 years of data modeling and of designing end-to-end data solutions across relational and non-relational databases.
• Preferred: a master's degree in computer science or a related field.
• Preferred: 8+ years of data engineering experience.
• Preferred: 5+ years of hands-on experience designing, deploying and running data workloads in AWS.
• 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 operating real-time or streaming data pipelines.
• 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 warehouses such as Snowflake or Redshift.
• Preferred: 4+ years of data modeling experience.
• Preferred: 3+ years of working in an agile development environment.
• Preferred: 3+ years of building user-centric reusable data products.
• Preferred: 3+ years of data observability work with tools such as Monte Carlo or Splunk, or data orchestration with tools such as Airflow or Dagster.

Conditions

The company will consider sponsoring a new qualified applicant for employment authorization for this role.

Base salary ranges, full-time annual, by location: Cambridge, MA and McLean, VA: $229,900 - $262,400. New York, NY: $250,800 - $286,200. Candidates hired elsewhere follow the range for their location, and the exact offer amount appears in the offer letter. Part-time pay is prorated to the agreed hours.

Applications will be accepted for at least 5 business days.

No agencies. The company is an equal opportunity employer.

Benefits

• Eligible for performance-based incentive pay, which may include cash bonuses and or long-term incentives, either discretionary or non-discretionary depending on the plan.
• Comprehensive health, financial and other benefits. Eligibility depends on full or part-time status, exempt status and management level.