The Motley Fool

The Motley Fool

Senior Data Engineer

United States - Remote · Senior

Sponsorship not specified$90k-$115kDetected 8 days ago
PythonCode ReviewGitSQLPostgreSQLSnowflakeAWSCloud PlatformsTerraformCI/CDGitHub ActionsRESTMachine Learningscikit-learnPandasNumPyAirflowData EngineeringData VisualizationLLMsRAGAgentic AIEmail MarketingForecasting

About the role

  • For 30 years, we've been helping people make better investment decisions through transparency, education, and a healthy dose of Foolish fun.
  • We're a fast-moving, collaborative team that values high-quality work, curiosity, and initiative.
  • We care deeply about what we do, and we're driven by the impact our work has on real people's financial futures.

Responsibilities

  • Design, build, and maintain robust ETL/ELT pipelines using Apache Airflow (MWAA).
  • Build "circuit breakers" into pipelines: automated data quality checks that halt downstream processing and alert the team via CloudWatch and Slack when anomalies are detected.
  • Implement AWS Lambda functions for lightweight, event-driven tasks such as triggering ingestion when files land in S3 or validating data payloads before loading.
  • Maintain and document the data catalog so institutional knowledge lives in the system, not in your head.
  • Design schemas, manage data loading via Stages and Snowpipe, and implement role-based access controls.
  • window functions, CTEs, recursive queries, pivots; to support investment reporting, performance attribution, and ad-hoc analysis.
  • Help design and maintain CI/CD workflows with GitHub Actions for automated testing, linting, and deployment of data pipelines, infrastructure, and application code.
  • Partner with investment and business teams to translate questions into data models, dashboards, and reports that drive strategic decisions using Tableau.
  • Design and build automated pipelines that pull data from source systems and render it into production-ready marketing outputs: one-pagers, pitch decks, email campaigns, and social content.
  • Be a resource for software engineers to build an AI layer on top of existing data infrastructure, enabling LLMs to securely query fund performance data via APIs and answer natural-language questions for internal stakeholders.

Requirements

  • Familiarity with financial research data vendors and feed/API products such as CapIQ Xpressfeed, FactSet, Bloomberg, Thomson Reuters/Refinitiv/LSEG, Russell or MSCI.
  • Hands-on experience with AWS CDK or Terraform.
  • Working knowledge of the
  • Experience profiling and optimizing queries across both OLAP (Snowflake) and OLTP (PostgreSQL/Aurora) systems.
  • Familiarity with EXPLAIN plans, indexing strategies, and database-level performance tuning.

Nice to have

  • Proven experience designing and operating ETL/ELT pipelines.
  • Apache Airflow and Lambda experience is a plus.
  • markdown files and prompt engineering.
  • Experience with RAG, knowledge bases, and embeddings is a plus.

Skills

  • Familiarity with financial business data and feed/API products from Broadridge, Morningstar and custodian banks and fund administrators.
  • ETL & Orchestration: Proven experience designing and operating ETL/ELT pipelines. Apache Airflow and Lambda experience is a plus.
  • Exposure to LLM integration patterns: markdown files and prompt engineering. Experience with RAG, knowledge bases, and embeddings is a plus.
  • Nice-to-Have/Pluses:
  • Cloud Fluency (AWS): Working knowledge of the AWS ecosystem: Lambda, ECS Fargate, Step Functions, S3, EventBridge, CloudWatch, and RDS.
  • Experience with data visualization tools (Tableau, Streamlit, or similar) for self-service analytics.
  • Background in data governance, data cataloging, or data lineage tooling.
  • Profile and optimize slow-running queries.
  • Leverage clustering keys, micro-partition pruning, materialized views, and result caching to minimize compute cost and maximize performance.
  • Cloud Infrastructure & CI/CD - 10%
  • Define and deploy cloud resources using Terraform or AWS CDK.
  • Treat infrastructure as software with version control, peer review, and automated testing.

Compensation

  • Below is our target compensation range. While we are budget conscious, we're also eager to find the right person for this role, so if your target is outside of this range, please don't hesitate to apply and we'd be happy to have a conversation.
  • Hourly Pay Range

Company info

  • Build reusable templates and automation frameworks to close the loop between our database and the materials our team uses to win and retain business.
  • That means pulling live data into branded one-pagers, generating narrative-driven slide decks, websites, populating email campaigns, and producing social-ready content.
  • Okay, but what will you actually do in this role?
  • Data Engineering & ETL - 35%
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This listing is sourced directly from The Motley Fool's careers page and normalized into a canonical job model.